Casal2 Test Case comparisons for HOK

1 HOK comparison of CASAL and Casal2 model configurations

This document compares the results of at least 2 CASAL model configurations (base and at least one sensitivity) and up to 8 Casal2 model configurations (3 BetaDiff, 2 CppAD, and 3 ADOL-C).

The CASAL model sensitivity 1 has a smaller tolerance value than the CASAL base model (1e-9 vs. 1e-6).

The Casal2 ADOL-C and BetaDiff low tolerance models have a smaller tolerance value than the CASAL base model (1e-9 vs. 1e-6). The Casal2 CppAD models have a tolerance value of 1e-9.

1.1 R environment

## [1] "Mon Mar  2 13:46:18 2020"

## R version 3.6.0 (2019-04-26)
## Platform: x86_64-redhat-linux-gnu (64-bit)
## Running under: CentOS Linux 7 (Core)
## 
## Matrix products: default
## BLAS/LAPACK: /usr/lib64/R/lib/libRblas.so
## 
## locale:
##  [1] LC_CTYPE=en_NZ.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_NZ.UTF-8        LC_COLLATE=en_NZ.UTF-8    
##  [5] LC_MONETARY=en_NZ.UTF-8    LC_MESSAGES=en_NZ.UTF-8   
##  [7] LC_PAPER=en_GB.UTF_8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=en_NZ.UTF-8 LC_IDENTIFICATION=C       
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] casal2_1.0     casal_2.30     devtools_2.2.2 usethis_1.5.1  rlist_0.4.6.1 
## [6] ggplot2_3.2.1 
## 
## loaded via a namespace (and not attached):
##  [1] Rcpp_1.0.3        pillar_1.4.3      compiler_3.6.0    remotes_2.1.1    
##  [5] prettyunits_1.1.1 tools_3.6.0       testthat_2.3.1    pkgload_1.0.2    
##  [9] pkgbuild_1.0.6    digest_0.6.25     memoise_1.1.0     evaluate_0.14    
## [13] lifecycle_0.1.0   tibble_2.1.3      gtable_0.3.0      pkgconfig_2.0.3  
## [17] rlang_0.4.5       cli_2.0.2         yaml_2.2.1        xfun_0.12        
## [21] withr_2.1.2       dplyr_0.8.4       stringr_1.4.0     knitr_1.28       
## [25] desc_1.2.0        fs_1.3.1          rprojroot_1.3-2   grid_3.6.0       
## [29] tidyselect_0.2.5  glue_1.3.1        data.table_1.12.8 R6_2.4.1         
## [33] processx_3.4.2    fansi_0.4.1       rmarkdown_2.1     sessioninfo_1.1.1
## [37] callr_3.4.2       purrr_0.3.3       magrittr_1.5      backports_1.1.5  
## [41] ps_1.3.2          ellipsis_0.3.0    scales_1.1.0      htmltools_0.4.0  
## [45] assertthat_0.2.1  colorspace_1.4-1  stringi_1.4.6     lazyeval_0.2.2   
## [49] munsell_0.5.0     crayon_1.3.4

1.2 CASAL and Casal2 model output

# read in CASAL MPD results
cas_mpd_filename <- file.path(base_dir, 'CASAL', mpd_run)
cas_mpd  <- casal::extract.mpd(cas_mpd_filename)
cas_corr <- casal::extract.correlation.matrix(cas_mpd_filename)

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

cas_conv <- get_convergence_information(cas_mpd_filename)
c1_quant <- cas_mpd$quantities

cas_mpd_sens1_filename <- file.path(base_dir, 'CASAL_sens1', mpd_run)
cas_mpd_sens1  <- casal::extract.mpd(cas_mpd_sens1_filename)
cas_sens1_corr <- casal::extract.correlation.matrix(cas_mpd_sens1_filename)

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

## Warning in casal.string.to.vector.of.numbers(lines[i]): NAs introduced by
## coercion

cas_sens1_conv <- get_convergence_information(cas_mpd_sens1_filename)
c1_sens1_quant <- cas_mpd_sens1$quantities

C2_subdir <- c('betadiff_casal_flags_on',
               'betadiff_casal_flags_off',
               'betadiff_casal_flags_on_low_tol',
               'cppad_casal_flags_on',
               'cppad_casal_flags_off',
               'adolc_casal_flags_on',
               'adolc_casal_flags_off',
               'adolc_casal_flags_on_low_tol')


# find the non-zero-sized parameter estimate files for the C2 models
C2_subdir <- unlist(sapply(C2_subdir, function(c_dir) if ( file.access(file.path(base_dir, 'Casal2', c_dir, params_est), 4) == 0 &
                                                           file.size(file.path(base_dir, 'Casal2', c_dir, params_est)) > 0 )
                                                         { return (c_dir) }, USE.NAMES=FALSE ))


num_C2_models <- length(C2_subdir)

C2_color <- c('blue', 'green3', 'red', 'gold', 'magenta', 'cyan', 'brown', 'orange')

# read in Casal2 MPD results
cas2_mpd <- list()
cas2_corr <- list()
cas2_conv <- list()
for (c in 1:num_C2_models)
{
    cas2_mpd_filename <- file.path(base_dir, 'Casal2', C2_subdir[c], mpd_run)
    cas2_mpd[[c]] <- casal2::extract.mpd(cas2_mpd_filename)

    cas2_corr[[c]] <- casal2::extract.correlation.matrix(mpd_out, file.path(base_dir, 'Casal2', C2_subdir[c]))

    cas2_conv[[c]] <- get_convergence_information(cas2_mpd_filename)
}

1.3 Tables

Tables of parameter estimates and objective function components for the CASAL and Casal2 model MPD results

CASAL parameter estimates

rownames	Base_Model	Sensitivity_1	Percent_Diff
q[CSacous].q	0.43115	0.43116	-0.003
q[WCacous].q	0.30025	0.30024	0.003
q[CRsum].q	0.07431	0.07431	0.007
q[SAsum].q	0.05925	0.05925	0.001
q[SAaut].q	0.06717	0.06717	0.002
relative_abundance[CRsumbio].cv_process_error	0.14048	0.14048	0.001
relative_abundance[SAsumbio].cv_process_error	0.43061	0.43061	-0.000
log_B0_total	14.33950	14.33950	0.000
B0_prop_stock1	0.32872	0.32871	0.003
natural_mortality.all	0.29598	0.29598	-0.002
selectivity[Wspsl].shift_a	-0.21743	-0.21744	-0.005
recruitment[E].YCS1	0.44781	0.44782	-0.001
recruitment[E].YCS2	0.72678	0.72680	-0.002
recruitment[E].YCS3	0.78452	0.78454	-0.002
recruitment[E].YCS4	1.35998	1.36001	-0.002
recruitment[E].YCS5	0.98774	0.98776	-0.002
recruitment[E].YCS6	0.32931	0.32932	-0.001
recruitment[E].YCS7	0.44722	0.44723	-0.001
recruitment[E].YCS8	0.26556	0.26556	-0.001
recruitment[E].YCS9	0.43418	0.43418	0.000
recruitment[E].YCS10	0.48804	0.48804	-0.001
recruitment[E].YCS11	0.39569	0.39570	-0.000
recruitment[E].YCS12	0.21791	0.21791	-0.000
recruitment[E].YCS13	1.03641	1.03640	0.001
recruitment[E].YCS14	0.95892	0.95891	0.001
recruitment[E].YCS15	0.42899	0.42899	-0.001
recruitment[E].YCS16	0.13810	0.13810	-0.001
recruitment[E].YCS17	0.37501	0.37500	0.002
recruitment[E].YCS18	0.39166	0.39164	0.005
recruitment[E].YCS19	0.38310	0.38310	0.000
recruitment[E].YCS20	0.56286	0.56285	0.002
recruitment[E].YCS21	0.26399	0.26399	0.000
recruitment[E].YCS22	0.28447	0.28447	0.000
recruitment[E].YCS23	0.45004	0.45003	0.001
recruitment[E].YCS24	0.25308	0.25307	0.001
recruitment[E].YCS25	0.06000	0.06000	0.000
recruitment[E].YCS26	0.46220	0.46220	0.001
recruitment[E].YCS27	0.16165	0.16165	-0.001
recruitment[E].YCS28	0.26690	0.26689	0.003
recruitment[E].YCS29	0.50038	0.50038	0.000
recruitment[E].YCS30	0.52003	0.52003	0.001
recruitment[E].YCS31	0.50883	0.50882	0.000
recruitment[E].YCS32	0.60056	0.60055	0.001
recruitment[E].YCS33	0.52215	0.52215	0.000
recruitment[E].YCS34	0.37302	0.37300	0.003
recruitment[E].YCS35	0.52681	0.52681	-0.000
recruitment[E].YCS36	0.15864	0.15864	0.001
recruitment[E].YCS37	0.66058	0.66058	0.000
recruitment[E].YCS38	0.15599	0.15600	-0.001
recruitment[E].YCS39	0.18584	0.18584	-0.001
recruitment[E].YCS40	0.73063	0.73062	0.001
recruitment[E].YCS41	0.73906	0.73900	0.008
recruitment[E].YCS42	1.19514	1.19515	-0.001
recruitment[W].YCS1	0.45702	0.45702	-0.000
recruitment[W].YCS2	0.82218	0.82218	0.000
recruitment[W].YCS3	0.67001	0.67000	0.000
recruitment[W].YCS4	0.65390	0.65390	0.000
recruitment[W].YCS5	0.46590	0.46590	0.001
recruitment[W].YCS6	0.51512	0.51512	-0.000
recruitment[W].YCS7	0.57824	0.57824	0.000
recruitment[W].YCS8	0.47328	0.47328	0.001
recruitment[W].YCS9	0.87191	0.87192	-0.002
recruitment[W].YCS10	0.83644	0.83646	-0.003
recruitment[W].YCS11	0.32024	0.32024	-0.002
recruitment[W].YCS12	0.16497	0.16497	0.001
recruitment[W].YCS13	1.47554	1.47555	-0.001
recruitment[W].YCS14	0.77274	0.77276	-0.002
recruitment[W].YCS15	0.08135	0.08134	0.000
recruitment[W].YCS16	0.08158	0.08158	0.001
recruitment[W].YCS17	0.89280	0.89280	0.000
recruitment[W].YCS18	1.26777	1.26778	-0.001
recruitment[W].YCS19	0.37722	0.37722	0.000
recruitment[W].YCS20	0.95940	0.95939	0.000
recruitment[W].YCS21	0.22113	0.22113	0.001
recruitment[W].YCS22	0.19718	0.19718	0.001
recruitment[W].YCS23	0.23794	0.23795	-0.003
recruitment[W].YCS24	0.20291	0.20292	-0.002
recruitment[W].YCS25	0.06000	0.06000	0.000
recruitment[W].YCS26	0.37304	0.37304	-0.002
recruitment[W].YCS27	0.09548	0.09548	-0.001
recruitment[W].YCS28	0.79558	0.79558	-0.000
recruitment[W].YCS29	0.46516	0.46517	-0.001
recruitment[W].YCS30	0.51662	0.51662	-0.001
recruitment[W].YCS31	0.51126	0.51126	-0.000
recruitment[W].YCS32	0.75544	0.75544	0.000
recruitment[W].YCS33	0.63892	0.63891	0.001
recruitment[W].YCS34	0.61686	0.61686	-0.001
recruitment[W].YCS35	0.57841	0.57841	0.001
recruitment[W].YCS36	0.14547	0.14547	-0.001
recruitment[W].YCS37	0.97479	0.97478	0.001
recruitment[W].YCS38	0.16016	0.16016	0.002
recruitment[W].YCS39	0.24444	0.24444	0.001
recruitment[W].YCS40	2.19661	2.19657	0.002
recruitment[W].YCS41	2.15201	2.15204	-0.001
recruitment[W].YCS42	1.19538	1.19539	-0.001
migration[Whome].rates_all1	0.32784	0.32783	0.003
migration[Whome].rates_all2	0.30780	0.30778	0.006
migration[Whome].rates_all3	0.47624	0.47620	0.007
migration[Whome].rates_all4	0.14184	0.14184	0.001
migration[Whome].rates_all5	0.46851	0.46836	0.033
migration[Whome].rates_all6	0.74978	0.75026	-0.064
migration[Whome].rates_all7	0.79469	0.78841	0.790
migration[Whome].rates_all8	1.00000	1.00000	0.000
migration[Espmg].rates_all1	0.00566	0.00566	0.002
migration[Espmg].rates_all2	0.16021	0.16021	0.002
migration[Espmg].rates_all3	0.32412	0.32411	0.002
migration[Espmg].rates_all4	0.43124	0.43123	0.002
migration[Espmg].rates_all5	0.38546	0.38546	0.002
migration[Espmg].rates_all6	0.46536	0.46535	0.002
migration[Espmg].rates_all7	0.59902	0.59902	0.001
migration[Espmg].rates_all8	0.60778	0.60778	0.001
migration[Wspmg].rates_all1	0.10614	0.10614	0.000
migration[Wspmg].rates_all2	0.28774	0.28774	-0.001
migration[Wspmg].rates_all3	0.27076	0.27076	0.000
migration[Wspmg].rates_all4	0.45525	0.45525	0.000
migration[Wspmg].rates_all5	0.48465	0.48466	-0.001
migration[Wspmg].rates_all6	0.52713	0.52711	0.005
migration[Wspmg].rates_all7	0.66056	0.66062	-0.009
migration[Wspmg].rates_all8	0.59628	0.59627	0.001
selectivity[Enspsl].all1	3.56717	3.56716	0.000
selectivity[Enspsl].all2	1.22109	1.22108	0.001
selectivity[Enspsl].all3	15.71130	15.71370	-0.015
selectivity[Wnspsl].all1	5.34113	5.34117	-0.001
selectivity[Wnspsl].all2	2.83932	2.83934	-0.001
selectivity[Wnspsl].all3	13.37880	13.37890	-0.001
selectivity[Espsl].all1	10.87880	10.87880	0.000
selectivity[Espsl].all2	11.67780	11.67750	0.003
selectivity[Espsl].all3	3.98159	3.98165	-0.002
selectivity[CRsl].all1	1.00000	1.00000	0.000
selectivity[CRsl].all2	1.00000	1.00000	0.000
selectivity[CRsl].all3	9.30026	9.30042	-0.002
selectivity[SAsl].all1	14.25200	14.25230	-0.002
selectivity[SAsl].all2	8.75543	8.75558	-0.002
selectivity[SAsl].all3	1.31548	1.31519	0.022

Casal2 parameter estimates

rownames	betadiff_casal_flags_on	betadiff_casal_flags_off	betadiff_casal_flags_on_low_tol	cppad_casal_flags_on	cppad_casal_flags_off	adolc_casal_flags_on	adolc_casal_flags_off	adolc_casal_flags_on_low_tol
catchability[CSacous].q	0.427	0.427	0.431	0.431	0.431	0.428	0.427	0.428
catchability[WCacous].q	0.313	0.313	0.300	0.300	0.300	0.312	0.313	0.312
catchability[CRsum].q	0.068	0.068	0.074	0.074	0.074	0.068	0.068	0.068
catchability[SAsum].q	0.067	0.067	0.059	0.059	0.059	0.067	0.067	0.067
catchability[SAaut].q	0.076	0.076	0.067	0.067	0.067	0.076	0.076	0.076
observation[CRsumbio].process_error	0.141	0.141	0.140	0.140	0.140	0.141	0.141	0.141
observation[SAsumbio].process_error	0.424	0.424	0.431	0.431	0.431	0.424	0.424	0.424
process[recruit_E].b0	548395.000	548395.000	555125.000	555125.000	555125.000	547497.000	548395.000	547497.000
process[recruit_W].b0	1082670.000	1082670.000	1133680.000	1133680.000	1133680.000	1083360.000	1082670.000	1083360.000
process[Instant_mortality].m{west.sa}	0.313	0.313	0.296	0.296	0.296	0.313	0.313	0.313
time_varying[shifted_mu].a	-0.229	-0.229	-0.217	-0.217	-0.217	-0.230	-0.229	-0.230
process[recruit_E].ycs_values{1975}	0.445	0.445	0.448	0.448	0.448	0.446	0.445	0.446
process[recruit_E].ycs_values{1976}	0.729	0.729	0.727	0.727	0.727	0.731	0.729	0.731
process[recruit_E].ycs_values{1977}	0.792	0.792	0.785	0.785	0.785	0.793	0.792	0.793
process[recruit_E].ycs_values{1978}	1.386	1.386	1.360	1.360	1.360	1.388	1.386	1.388
process[recruit_E].ycs_values{1979}	1.003	1.003	0.988	0.988	0.988	1.004	1.003	1.004
process[recruit_E].ycs_values{1980}	0.334	0.334	0.329	0.329	0.329	0.335	0.334	0.335
process[recruit_E].ycs_values{1981}	0.455	0.455	0.447	0.447	0.447	0.455	0.455	0.455
process[recruit_E].ycs_values{1982}	0.270	0.270	0.266	0.266	0.266	0.270	0.270	0.270
process[recruit_E].ycs_values{1983}	0.441	0.441	0.434	0.434	0.434	0.441	0.441	0.441
process[recruit_E].ycs_values{1984}	0.494	0.494	0.488	0.488	0.488	0.494	0.494	0.494
process[recruit_E].ycs_values{1985}	0.400	0.400	0.396	0.396	0.396	0.400	0.400	0.400
process[recruit_E].ycs_values{1986}	0.220	0.220	0.218	0.218	0.218	0.220	0.220	0.220
process[recruit_E].ycs_values{1987}	1.041	1.041	1.036	1.036	1.036	1.041	1.041	1.041
process[recruit_E].ycs_values{1988}	0.963	0.963	0.959	0.959	0.959	0.963	0.963	0.963
process[recruit_E].ycs_values{1989}	0.431	0.431	0.429	0.429	0.429	0.431	0.431	0.431
process[recruit_E].ycs_values{1990}	0.138	0.138	0.138	0.138	0.138	0.138	0.138	0.138
process[recruit_E].ycs_values{1991}	0.374	0.374	0.375	0.375	0.375	0.373	0.374	0.373
process[recruit_E].ycs_values{1992}	0.389	0.389	0.392	0.392	0.392	0.388	0.389	0.388
process[recruit_E].ycs_values{1993}	0.380	0.380	0.383	0.383	0.383	0.380	0.380	0.380
process[recruit_E].ycs_values{1994}	0.558	0.558	0.563	0.563	0.563	0.557	0.558	0.557
process[recruit_E].ycs_values{1995}	0.262	0.262	0.264	0.264	0.264	0.262	0.262	0.262
process[recruit_E].ycs_values{1996}	0.283	0.283	0.284	0.284	0.284	0.282	0.283	0.282
process[recruit_E].ycs_values{1997}	0.448	0.448	0.450	0.450	0.450	0.448	0.448	0.448
process[recruit_E].ycs_values{1998}	0.253	0.253	0.253	0.253	0.253	0.252	0.253	0.252
process[recruit_E].ycs_values{1999}	0.060	0.060	0.060	0.060	0.060	0.060	0.060	0.060
process[recruit_E].ycs_values{2000}	0.460	0.460	0.462	0.462	0.462	0.460	0.460	0.460
process[recruit_E].ycs_values{2001}	0.161	0.161	0.162	0.162	0.162	0.161	0.161	0.161
process[recruit_E].ycs_values{2002}	0.266	0.266	0.267	0.267	0.267	0.266	0.266	0.266
process[recruit_E].ycs_values{2003}	0.500	0.500	0.500	0.500	0.500	0.499	0.500	0.499
process[recruit_E].ycs_values{2004}	0.521	0.521	0.520	0.520	0.520	0.520	0.521	0.520
process[recruit_E].ycs_values{2005}	0.508	0.508	0.509	0.509	0.509	0.508	0.508	0.508
process[recruit_E].ycs_values{2006}	0.600	0.600	0.601	0.601	0.601	0.600	0.600	0.600
process[recruit_E].ycs_values{2007}	0.521	0.521	0.522	0.522	0.522	0.521	0.521	0.521
process[recruit_E].ycs_values{2008}	0.371	0.371	0.373	0.373	0.373	0.370	0.371	0.370
process[recruit_E].ycs_values{2009}	0.528	0.528	0.527	0.527	0.527	0.528	0.528	0.528
process[recruit_E].ycs_values{2010}	0.157	0.157	0.159	0.159	0.159	0.157	0.157	0.157
process[recruit_E].ycs_values{2011}	0.660	0.660	0.661	0.661	0.661	0.660	0.660	0.660
process[recruit_E].ycs_values{2012}	0.156	0.156	0.156	0.156	0.156	0.156	0.156	0.156
process[recruit_E].ycs_values{2013}	0.185	0.185	0.186	0.186	0.186	0.185	0.185	0.185
process[recruit_E].ycs_values{2014}	0.728	0.728	0.731	0.731	0.731	0.728	0.728	0.728
process[recruit_E].ycs_values{2015}	0.756	0.756	0.739	0.739	0.739	0.752	0.756	0.752
process[recruit_E].ycs_values{2016}	1.189	1.189	1.195	1.195	1.195	1.189	1.189	1.189
process[recruit_W].ycs_values{1975}	0.459	0.459	0.457	0.457	0.457	0.459	0.459	0.459
process[recruit_W].ycs_values{1976}	0.814	0.814	0.822	0.822	0.822	0.814	0.814	0.814
process[recruit_W].ycs_values{1977}	0.685	0.685	0.670	0.670	0.670	0.685	0.685	0.685
process[recruit_W].ycs_values{1978}	0.669	0.669	0.654	0.654	0.654	0.669	0.669	0.669
process[recruit_W].ycs_values{1979}	0.473	0.473	0.466	0.466	0.466	0.473	0.473	0.473
process[recruit_W].ycs_values{1980}	0.521	0.521	0.515	0.515	0.515	0.521	0.521	0.521
process[recruit_W].ycs_values{1981}	0.583	0.583	0.578	0.578	0.578	0.583	0.583	0.583
process[recruit_W].ycs_values{1982}	0.475	0.475	0.473	0.473	0.473	0.474	0.475	0.474
process[recruit_W].ycs_values{1983}	0.873	0.873	0.872	0.872	0.872	0.874	0.873	0.874
process[recruit_W].ycs_values{1984}	0.836	0.836	0.836	0.836	0.836	0.837	0.836	0.837
process[recruit_W].ycs_values{1985}	0.319	0.319	0.320	0.320	0.320	0.320	0.319	0.320
process[recruit_W].ycs_values{1986}	0.165	0.165	0.165	0.165	0.165	0.165	0.165	0.165
process[recruit_W].ycs_values{1987}	1.480	1.480	1.476	1.476	1.476	1.481	1.480	1.481
process[recruit_W].ycs_values{1988}	0.775	0.775	0.773	0.773	0.773	0.775	0.775	0.775
process[recruit_W].ycs_values{1989}	0.081	0.081	0.081	0.081	0.081	0.081	0.081	0.081
process[recruit_W].ycs_values{1990}	0.082	0.082	0.082	0.082	0.082	0.082	0.082	0.082
process[recruit_W].ycs_values{1991}	0.892	0.892	0.893	0.893	0.893	0.892	0.892	0.892
process[recruit_W].ycs_values{1992}	1.268	1.268	1.268	1.268	1.268	1.268	1.268	1.268
process[recruit_W].ycs_values{1993}	0.377	0.377	0.377	0.377	0.377	0.376	0.377	0.376
process[recruit_W].ycs_values{1994}	0.956	0.956	0.959	0.959	0.959	0.956	0.956	0.956
process[recruit_W].ycs_values{1995}	0.220	0.220	0.221	0.221	0.221	0.220	0.220	0.220
process[recruit_W].ycs_values{1996}	0.196	0.196	0.197	0.197	0.197	0.196	0.196	0.196
process[recruit_W].ycs_values{1997}	0.236	0.236	0.238	0.238	0.238	0.237	0.236	0.237
process[recruit_W].ycs_values{1998}	0.200	0.200	0.203	0.203	0.203	0.201	0.200	0.201
process[recruit_W].ycs_values{1999}	0.060	0.060	0.060	0.060	0.060	0.060	0.060	0.060
process[recruit_W].ycs_values{2000}	0.371	0.371	0.373	0.373	0.373	0.371	0.371	0.371
process[recruit_W].ycs_values{2001}	0.095	0.095	0.095	0.095	0.095	0.095	0.095	0.095
process[recruit_W].ycs_values{2002}	0.796	0.796	0.796	0.796	0.796	0.796	0.796	0.796
process[recruit_W].ycs_values{2003}	0.466	0.466	0.465	0.465	0.465	0.466	0.466	0.466
process[recruit_W].ycs_values{2004}	0.518	0.518	0.517	0.517	0.517	0.518	0.518	0.518
process[recruit_W].ycs_values{2005}	0.513	0.513	0.511	0.511	0.511	0.513	0.513	0.513
process[recruit_W].ycs_values{2006}	0.755	0.755	0.755	0.755	0.755	0.755	0.755	0.755
process[recruit_W].ycs_values{2007}	0.637	0.637	0.639	0.639	0.639	0.637	0.637	0.637
process[recruit_W].ycs_values{2008}	0.616	0.616	0.617	0.617	0.617	0.616	0.616	0.616
process[recruit_W].ycs_values{2009}	0.573	0.573	0.578	0.578	0.578	0.573	0.573	0.573
process[recruit_W].ycs_values{2010}	0.146	0.146	0.145	0.145	0.145	0.146	0.146	0.146
process[recruit_W].ycs_values{2011}	0.967	0.967	0.975	0.975	0.975	0.967	0.967	0.967
process[recruit_W].ycs_values{2012}	0.159	0.159	0.160	0.160	0.160	0.159	0.159	0.159
process[recruit_W].ycs_values{2013}	0.244	0.244	0.244	0.244	0.244	0.244	0.244	0.244
process[recruit_W].ycs_values{2014}	2.187	2.187	2.197	2.197	2.197	2.185	2.187	2.185
process[recruit_W].ycs_values{2015}	2.148	2.148	2.152	2.152	2.152	2.150	2.148	2.150
process[recruit_W].ycs_values{2016}	1.189	1.189	1.195	1.195	1.195	1.190	1.189	1.190
selectivity[sel_Whome].v{1}	0.322	0.322	0.328	0.328	0.328	0.321	0.322	0.321
selectivity[sel_Whome].v{2}	0.285	0.285	0.308	0.308	0.308	0.284	0.285	0.284
selectivity[sel_Whome].v{3}	0.460	0.460	0.476	0.476	0.476	0.458	0.460	0.458
selectivity[sel_Whome].v{4}	0.135	0.135	0.142	0.142	0.142	0.135	0.135	0.135
selectivity[sel_Whome].v{5}	0.438	0.438	0.468	0.468	0.468	0.432	0.438	0.432
selectivity[sel_Whome].v{6}	0.708	0.708	0.750	0.750	0.750	0.719	0.708	0.719
selectivity[sel_Whome].v{7}	1.000	1.000	0.788	0.788	0.788	0.760	1.000	0.760
selectivity[sel_Espmg].v{1}	0.006	0.006	0.006	0.006	0.006	0.006	0.006	0.006
selectivity[sel_Espmg].v{2}	0.159	0.159	0.160	0.160	0.160	0.159	0.159	0.159
selectivity[sel_Espmg].v{3}	0.321	0.321	0.324	0.324	0.324	0.321	0.321	0.321
selectivity[sel_Espmg].v{4}	0.425	0.425	0.431	0.431	0.431	0.425	0.425	0.425
selectivity[sel_Espmg].v{5}	0.380	0.380	0.385	0.385	0.385	0.379	0.380	0.379
selectivity[sel_Espmg].v{6}	0.459	0.459	0.465	0.465	0.465	0.458	0.459	0.458
selectivity[sel_Espmg].v{7}	0.591	0.591	0.599	0.599	0.599	0.590	0.591	0.590
selectivity[sel_Espmg].v{8}	0.611	0.611	0.608	0.608	0.608	0.611	0.611	0.611
selectivity[sel_Wspmg].v{1}	0.106	0.106	0.106	0.106	0.106	0.106	0.106	0.106
selectivity[sel_Wspmg].v{2}	0.291	0.291	0.288	0.288	0.288	0.291	0.291	0.291
selectivity[sel_Wspmg].v{3}	0.271	0.271	0.271	0.271	0.271	0.271	0.271	0.271
selectivity[sel_Wspmg].v{4}	0.455	0.455	0.455	0.455	0.455	0.455	0.455	0.455
selectivity[sel_Wspmg].v{5}	0.484	0.484	0.485	0.485	0.485	0.484	0.484	0.484
selectivity[sel_Wspmg].v{6}	0.525	0.525	0.527	0.527	0.527	0.524	0.525	0.524
selectivity[sel_Wspmg].v{7}	0.653	0.653	0.661	0.661	0.661	0.656	0.653	0.656
selectivity[sel_Wspmg].v{8}	0.602	0.602	0.596	0.596	0.596	0.601	0.602	0.601
selectivity[Enspsl].mu	3.573	3.573	3.567	3.567	3.567	3.572	3.573	3.572
selectivity[Enspsl].sigma_l	1.222	1.222	1.221	1.221	1.221	1.222	1.222	1.222
selectivity[Enspsl].sigma_r	50.000	50.000	15.714	15.714	15.714	50.000	50.000	50.000
selectivity[Wnspsl].mu	5.328	5.328	5.341	5.341	5.341	5.330	5.328	5.330
selectivity[Wnspsl].sigma_l	2.778	2.778	2.839	2.839	2.839	2.778	2.778	2.778
selectivity[Wnspsl].sigma_r	50.000	50.000	13.379	13.379	13.379	50.000	49.989	50.000
selectivity[Espsl].mu	11.257	11.257	10.879	10.879	10.879	11.255	11.257	11.255
selectivity[Espsl].sigma_l	10.867	10.867	11.678	11.678	11.678	10.859	10.867	10.859
selectivity[Espsl].sigma_r	4.026	4.026	3.982	3.982	3.982	4.029	4.026	4.029
selectivity[CRsl].mu	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000
selectivity[CRsl].sigma_l	46.484	46.481	45.986	25.500	25.500	46.483	46.483	46.483
selectivity[CRsl].sigma_r	10.093	10.093	9.300	9.300	9.300	10.088	10.093	10.088
selectivity[SAsl].mu	14.868	14.868	14.252	14.252	14.252	14.865	14.868	14.865
selectivity[SAsl].sigma_l	8.695	8.695	8.756	8.756	8.756	8.693	8.695	8.693
selectivity[SAsl].sigma_r	1.000	1.000	1.315	1.315	1.315	1.000	1.000	1.000

Casal2 parameter estimates: Percent Difference from betadiff_casal_flags_on

rownames	betadiff_casal_flags_on	betadiff_casal_flags_off	betadiff_casal_flags_on_low_tol	cppad_casal_flags_on	cppad_casal_flags_off	adolc_casal_flags_on	adolc_casal_flags_off	adolc_casal_flags_on_low_tol
catchability[CSacous].q	0.000	0.000	-0.918	-0.918	-0.918	-0.145	0.000	-0.145
catchability[WCacous].q	0.000	0.000	4.027	4.027	4.027	0.128	0.000	0.128
catchability[CRsum].q	0.000	0.000	-8.765	-8.765	-8.765	0.298	-0.000	0.298
catchability[SAsum].q	0.000	0.000	11.797	11.797	11.797	0.172	0.000	0.172
catchability[SAaut].q	0.000	0.000	11.363	11.363	11.363	0.188	0.000	0.188
observation[CRsumbio].process_error	0.000	0.000	0.328	0.328	0.328	0.035	0.000	0.035
observation[SAsumbio].process_error	0.000	-0.000	-1.645	-1.645	-1.645	-0.040	0.000	-0.040
process[recruit_E].b0	0.000	0.000	-1.227	-1.227	-1.227	0.164	0.000	0.164
process[recruit_W].b0	0.000	0.000	-4.712	-4.712	-4.712	-0.064	0.000	-0.064
process[Instant_mortality].m{west.sa}	0.000	0.000	5.349	5.349	5.349	-0.070	0.000	-0.070
time_varying[shifted_mu].a	0.000	0.000	5.135	5.135	5.135	-0.166	0.000	-0.166
process[recruit_E].ycs_values{1975}	0.000	0.000	-0.549	-0.549	-0.549	-0.117	0.001	-0.117
process[recruit_E].ycs_values{1976}	0.000	0.000	0.355	0.355	0.355	-0.156	-0.001	-0.156
process[recruit_E].ycs_values{1977}	0.000	0.000	0.982	0.982	0.982	-0.127	0.001	-0.127
process[recruit_E].ycs_values{1978}	0.000	0.001	1.907	1.907	1.907	-0.131	0.001	-0.132
process[recruit_E].ycs_values{1979}	0.000	0.000	1.485	1.485	1.485	-0.107	0.000	-0.107
process[recruit_E].ycs_values{1980}	0.000	0.000	1.512	1.512	1.512	-0.073	0.000	-0.073
process[recruit_E].ycs_values{1981}	0.000	0.000	1.712	1.712	1.712	-0.072	0.000	-0.072
process[recruit_E].ycs_values{1982}	0.000	0.000	1.551	1.551	1.551	-0.055	0.000	-0.055
process[recruit_E].ycs_values{1983}	0.000	0.000	1.559	1.559	1.559	0.013	0.000	0.013
process[recruit_E].ycs_values{1984}	0.000	0.000	1.229	1.229	1.229	-0.022	0.000	-0.022
process[recruit_E].ycs_values{1985}	0.000	0.000	1.102	1.102	1.102	-0.009	0.000	-0.009
process[recruit_E].ycs_values{1986}	0.000	0.000	0.850	0.850	0.850	-0.022	-0.000	-0.022
process[recruit_E].ycs_values{1987}	0.000	0.000	0.472	0.472	0.472	0.035	0.000	0.035
process[recruit_E].ycs_values{1988}	0.000	0.000	0.471	0.471	0.471	0.032	-0.000	0.032
process[recruit_E].ycs_values{1989}	0.000	0.000	0.455	0.455	0.455	-0.040	0.000	-0.040
process[recruit_E].ycs_values{1990}	0.000	0.000	-0.101	-0.101	-0.101	-0.009	0.000	-0.009
process[recruit_E].ycs_values{1991}	0.000	0.000	-0.307	-0.307	-0.307	0.135	0.000	0.135
process[recruit_E].ycs_values{1992}	0.000	0.000	-0.787	-0.787	-0.787	0.259	-0.000	0.259
process[recruit_E].ycs_values{1993}	0.000	0.000	-0.831	-0.831	-0.831	0.016	0.000	0.016
process[recruit_E].ycs_values{1994}	0.000	0.000	-0.880	-0.880	-0.880	0.122	-0.000	0.122
process[recruit_E].ycs_values{1995}	0.000	0.000	-0.843	-0.843	-0.843	-0.002	0.000	-0.002
process[recruit_E].ycs_values{1996}	0.000	0.000	-0.695	-0.695	-0.695	0.008	0.000	0.008
process[recruit_E].ycs_values{1997}	0.000	0.000	-0.496	-0.496	-0.496	0.049	0.000	0.049
process[recruit_E].ycs_values{1998}	0.000	0.000	-0.170	-0.170	-0.170	0.061	0.000	0.061
process[recruit_E].ycs_values{1999}	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
process[recruit_E].ycs_values{2000}	0.000	0.000	-0.449	-0.449	-0.449	0.057	0.000	0.057
process[recruit_E].ycs_values{2001}	0.000	0.000	-0.489	-0.489	-0.489	-0.007	0.000	-0.007
process[recruit_E].ycs_values{2002}	0.000	0.000	-0.294	-0.294	-0.294	0.191	0.000	0.191
process[recruit_E].ycs_values{2003}	0.000	0.000	-0.159	-0.159	-0.159	0.031	0.000	0.031
process[recruit_E].ycs_values{2004}	0.000	0.000	0.096	0.096	0.096	0.043	-0.000	0.043
process[recruit_E].ycs_values{2005}	0.000	0.000	-0.233	-0.233	-0.233	0.021	0.000	0.021
process[recruit_E].ycs_values{2006}	0.000	0.000	-0.070	-0.070	-0.070	0.046	-0.000	0.046
process[recruit_E].ycs_values{2007}	0.000	0.000	-0.245	-0.245	-0.245	0.014	-0.000	0.014
process[recruit_E].ycs_values{2008}	0.000	0.000	-0.500	-0.500	-0.500	0.184	0.000	0.184
process[recruit_E].ycs_values{2009}	0.000	0.000	0.206	0.206	0.206	0.007	0.000	0.007
process[recruit_E].ycs_values{2010}	0.000	0.000	-1.074	-1.074	-1.074	0.032	-0.001	0.032
process[recruit_E].ycs_values{2011}	0.000	0.000	-0.017	-0.017	-0.017	0.028	0.000	0.028
process[recruit_E].ycs_values{2012}	0.000	-0.001	-0.294	-0.294	-0.294	-0.031	-0.001	-0.031
process[recruit_E].ycs_values{2013}	0.000	0.000	-0.355	-0.355	-0.355	0.002	0.000	0.002
process[recruit_E].ycs_values{2014}	0.000	0.000	-0.299	-0.299	-0.299	0.049	0.000	0.049
process[recruit_E].ycs_values{2015}	0.000	0.000	2.230	2.230	2.230	0.469	-0.002	0.469
process[recruit_E].ycs_values{2016}	0.000	0.000	-0.529	-0.529	-0.529	-0.045	0.000	-0.045
process[recruit_W].ycs_values{1975}	0.000	-0.000	0.365	0.365	0.365	-0.006	0.001	-0.005
process[recruit_W].ycs_values{1976}	0.000	-0.000	-0.978	-0.978	-0.978	-0.014	-0.001	-0.014
process[recruit_W].ycs_values{1977}	0.000	0.000	2.210	2.210	2.210	0.031	0.000	0.031
process[recruit_W].ycs_values{1978}	0.000	0.000	2.311	2.311	2.311	0.048	-0.000	0.048
process[recruit_W].ycs_values{1979}	0.000	0.000	1.517	1.517	1.517	0.067	-0.000	0.067
process[recruit_W].ycs_values{1980}	0.000	0.000	1.061	1.061	1.061	0.023	-0.000	0.023
process[recruit_W].ycs_values{1981}	0.000	0.000	0.892	0.892	0.892	0.027	-0.000	0.027
process[recruit_W].ycs_values{1982}	0.000	0.000	0.284	0.284	0.284	0.047	0.000	0.047
process[recruit_W].ycs_values{1983}	0.000	-0.000	0.133	0.133	0.133	-0.076	-0.000	-0.076
process[recruit_W].ycs_values{1984}	0.000	0.000	-0.016	-0.016	-0.016	-0.125	0.000	-0.125
process[recruit_W].ycs_values{1985}	0.000	0.000	-0.257	-0.257	-0.257	-0.103	0.000	-0.103
process[recruit_W].ycs_values{1986}	0.000	0.000	-0.021	-0.021	-0.021	0.055	0.000	0.055
process[recruit_W].ycs_values{1987}	0.000	0.000	0.305	0.305	0.305	-0.040	0.000	-0.039
process[recruit_W].ycs_values{1988}	0.000	0.000	0.229	0.229	0.229	-0.099	0.000	-0.099
process[recruit_W].ycs_values{1989}	0.000	0.000	0.160	0.160	0.160	0.003	0.000	0.003
process[recruit_W].ycs_values{1990}	0.000	0.000	0.304	0.304	0.304	0.037	0.000	0.037
process[recruit_W].ycs_values{1991}	0.000	0.000	-0.093	-0.093	-0.093	0.009	-0.000	0.009
process[recruit_W].ycs_values{1992}	0.000	0.000	-0.017	-0.017	-0.017	-0.021	0.000	-0.021
process[recruit_W].ycs_values{1993}	0.000	0.000	-0.185	-0.185	-0.185	0.011	0.000	0.011
process[recruit_W].ycs_values{1994}	0.000	-0.000	-0.377	-0.377	-0.377	0.023	-0.000	0.023
process[recruit_W].ycs_values{1995}	0.000	0.000	-0.392	-0.392	-0.392	0.054	0.000	0.054
process[recruit_W].ycs_values{1996}	0.000	0.000	-0.440	-0.440	-0.440	0.028	0.000	0.028
process[recruit_W].ycs_values{1997}	0.000	0.000	-0.643	-0.643	-0.643	-0.147	0.000	-0.147
process[recruit_W].ycs_values{1998}	0.000	0.000	-1.251	-1.251	-1.251	-0.099	0.000	-0.099
process[recruit_W].ycs_values{1999}	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
process[recruit_W].ycs_values{2000}	0.000	0.000	-0.581	-0.581	-0.581	-0.118	0.000	-0.118
process[recruit_W].ycs_values{2001}	0.000	0.000	-0.446	-0.446	-0.446	-0.037	0.000	-0.037
process[recruit_W].ycs_values{2002}	0.000	0.000	-0.007	-0.007	-0.007	-0.029	0.000	-0.029
process[recruit_W].ycs_values{2003}	0.000	-0.000	0.114	0.114	0.114	-0.039	-0.000	-0.039
process[recruit_W].ycs_values{2004}	0.000	0.000	0.191	0.191	0.191	-0.045	0.000	-0.045
process[recruit_W].ycs_values{2005}	0.000	-0.000	0.349	0.349	0.349	-0.017	-0.000	-0.017
process[recruit_W].ycs_values{2006}	0.000	0.000	-0.091	-0.091	-0.091	-0.015	0.000	-0.015
process[recruit_W].ycs_values{2007}	0.000	0.000	-0.312	-0.312	-0.312	0.026	0.000	0.026
process[recruit_W].ycs_values{2008}	0.000	0.000	-0.198	-0.198	-0.198	-0.080	-0.000	-0.081
process[recruit_W].ycs_values{2009}	0.000	-0.000	-0.934	-0.934	-0.934	0.024	-0.000	0.024
process[recruit_W].ycs_values{2010}	0.000	-0.001	0.482	0.482	0.482	-0.056	-0.001	-0.056
process[recruit_W].ycs_values{2011}	0.000	0.000	-0.796	-0.796	-0.796	0.041	0.000	0.041
process[recruit_W].ycs_values{2012}	0.000	0.000	-0.674	-0.674	-0.674	0.075	0.000	0.075
process[recruit_W].ycs_values{2013}	0.000	0.000	-0.172	-0.172	-0.172	0.052	0.000	0.052
process[recruit_W].ycs_values{2014}	0.000	0.000	-0.460	-0.460	-0.460	0.081	0.000	0.081
process[recruit_W].ycs_values{2015}	0.000	0.000	-0.207	-0.207	-0.207	-0.098	0.000	-0.098
process[recruit_W].ycs_values{2016}	0.000	0.000	-0.530	-0.530	-0.530	-0.045	0.000	-0.045
selectivity[sel_Whome].v{1}	0.000	0.000	-1.833	-1.833	-1.833	0.177	0.000	0.177
selectivity[sel_Whome].v{2}	0.000	0.000	-8.027	-8.027	-8.027	0.370	-0.000	0.370
selectivity[sel_Whome].v{3}	0.000	-0.000	-3.584	-3.584	-3.584	0.429	-0.000	0.429
selectivity[sel_Whome].v{4}	0.000	0.001	-4.690	-4.690	-4.690	0.341	-0.004	0.341
selectivity[sel_Whome].v{5}	0.000	-0.000	-6.974	-6.974	-6.974	1.401	0.001	1.401
selectivity[sel_Whome].v{6}	0.000	-0.001	-5.942	-5.942	-5.942	-1.514	-0.005	-1.514
selectivity[sel_Whome].v{7}	0.000	-0.004	21.145	21.145	21.145	24.025	-0.013	24.025
selectivity[sel_Espmg].v{1}	0.000	0.000	-0.332	-0.332	-0.332	0.080	0.000	0.080
selectivity[sel_Espmg].v{2}	0.000	0.000	-0.683	-0.683	-0.683	0.073	0.000	0.073
selectivity[sel_Espmg].v{3}	0.000	0.000	-1.028	-1.028	-1.028	0.078	0.000	0.078
selectivity[sel_Espmg].v{4}	0.000	0.000	-1.354	-1.354	-1.354	0.079	0.000	0.079
selectivity[sel_Espmg].v{5}	0.000	0.000	-1.563	-1.563	-1.563	0.069	0.000	0.069
selectivity[sel_Espmg].v{6}	0.000	0.000	-1.436	-1.436	-1.436	0.063	0.000	0.063
selectivity[sel_Espmg].v{7}	0.000	0.000	-1.389	-1.389	-1.389	0.062	-0.000	0.062
selectivity[sel_Espmg].v{8}	0.000	0.000	0.528	0.528	0.528	0.060	0.000	0.060
selectivity[sel_Wspmg].v{1}	0.000	0.000	-0.552	-0.552	-0.552	0.033	0.001	0.033
selectivity[sel_Wspmg].v{2}	0.000	0.000	1.242	1.242	1.242	-0.010	0.000	-0.010
selectivity[sel_Wspmg].v{3}	0.000	0.000	-0.029	-0.029	-0.029	0.008	0.000	0.008
selectivity[sel_Wspmg].v{4}	0.000	0.000	0.004	0.004	0.004	0.017	0.000	0.017
selectivity[sel_Wspmg].v{5}	0.000	0.000	-0.092	-0.092	-0.092	-0.026	0.000	-0.026
selectivity[sel_Wspmg].v{6}	0.000	0.000	-0.409	-0.409	-0.409	0.187	0.000	0.187
selectivity[sel_Wspmg].v{7}	0.000	0.000	-1.170	-1.170	-1.170	-0.449	0.000	-0.449
selectivity[sel_Wspmg].v{8}	0.000	0.000	0.875	0.875	0.875	0.087	0.000	0.087
selectivity[Enspsl].mu	0.000	0.000	0.168	0.168	0.168	0.025	0.000	0.025
selectivity[Enspsl].sigma_l	0.000	0.000	0.112	0.112	0.112	0.032	0.000	0.032
selectivity[Enspsl].sigma_r	0.000	0.001	68.573	68.573	68.573	0.000	0.000	0.000
selectivity[Wnspsl].mu	0.000	0.000	-0.240	-0.240	-0.240	-0.021	0.000	-0.021
selectivity[Wnspsl].sigma_l	0.000	0.000	-2.203	-2.203	-2.203	-0.011	0.000	-0.011
selectivity[Wnspsl].sigma_r	0.000	0.000	73.242	73.242	73.242	0.000	0.022	0.000
selectivity[Espsl].mu	0.000	0.000	3.357	3.357	3.357	0.018	0.000	0.018
selectivity[Espsl].sigma_l	0.000	0.000	-7.454	-7.454	-7.454	0.074	0.000	0.074
selectivity[Espsl].sigma_r	0.000	0.000	1.108	1.108	1.108	-0.071	0.000	-0.071
selectivity[CRsl].mu	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
selectivity[CRsl].sigma_l	0.000	0.006	1.070	45.142	45.142	0.001	0.000	0.001
selectivity[CRsl].sigma_r	0.000	0.000	7.851	7.851	7.851	0.050	0.000	0.050
selectivity[SAsl].mu	0.000	0.000	4.144	4.144	4.144	0.025	0.000	0.025
selectivity[SAsl].sigma_l	0.000	0.000	-0.700	-0.700	-0.700	0.022	-0.000	0.022
selectivity[SAsl].sigma_r	0.000	0.000	-31.519	-31.519	-31.519	0.000	0.000	0.000

CASAL objective function component values

Component	Base_Model	Sensitivity_1
CRsumbio	-31.032	-31.032
CSacous	-9.835	-9.836
SAautbio	-3.984	-3.984
SAsumbio	-6.146	-6.146
WCacous	-5.916	-5.916
CRsumage	323.850	323.850
SAautage	35.117	35.118
SAsumage	221.149	221.150
EnspOLF	24.276	24.276
Enspage	256.069	256.068
Espage	581.502	581.502
WnspOLF	70.250	70.250
Wnspage	157.004	157.004
Wspage	364.751	364.751
pspawn	-13.129	-13.129
pspawn_1993	-6.015	-6.015
prior_on_q[CSacous].q	-0.839	-0.839
prior_on_q[WCacous].q	-1.202	-1.202
prior_on_q[CRsum].q	-2.207	-2.207
prior_on_q[SAsum].q	-1.557	-1.557
prior_on_q[SAaut].q	-1.762	-1.762
prior_on_relative_abundance[CRsumbio].cv_process_error	0.000	0.000
prior_on_relative_abundance[SAsumbio].cv_process_error	0.000	0.000
prior_on_log_B0_total	0.000	0.000
prior_on_B0_prop_stock1	12.555	12.555
prior_on_natural_mortality.all	-1.217	-1.217
prior_on_selectivity[Wspsl].shift_a	0.378	0.378
prior_on_recruitment[E].YCS	-13.750	-13.750
prior_on_recruitment[W].YCS	-1.785	-1.785
prior_on_migration[Whome].rates_all	0.000	0.000
prior_on_migration[Espmg].rates_all	0.000	0.000
prior_on_migration[Wspmg].rates_all	0.000	0.000
prior_on_selectivity[Enspsl].all	0.000	0.000
prior_on_selectivity[Wnspsl].all	0.000	0.000
prior_on_selectivity[Espsl].all	0.000	0.000
prior_on_selectivity[CRsl].all	0.000	0.000
prior_on_selectivity[SAsl].all	0.000	0.000
Umax_Ensp1	0.000	0.000
Umax_Ensp2	0.000	0.000
Umax_Wnsp1	0.000	0.000
Umax_Wnsp2	0.000	0.000
Umax_Esp	0.000	0.000
Umax_Wsp	0.000	0.000
YCS.eq.16	0.000	0.000
sp.migr	0.013	0.013
Total	1946.540	1946.540

Casal2 objective function component values

rownames	betadiff_casal_flags_on	betadiff_casal_flags_off	betadiff_casal_flags_on_low_tol	cppad_casal_flags_on	cppad_casal_flags_off	adolc_casal_flags_on	adolc_casal_flags_off	adolc_casal_flags_on_low_tol
observation->CSacous-1991	2.342	2.342	2.404	2.404	2.404	2.344	2.342	2.344
observation->CSacous-1993	-0.577	-0.577	-0.588	-0.588	-0.588	-0.577	-0.577	-0.577
observation->CSacous-1994	-0.016	-0.016	-0.030	-0.030	-0.030	-0.016	-0.016	-0.016
observation->CSacous-1995	-0.562	-0.562	-0.567	-0.567	-0.567	-0.562	-0.562	-0.562
observation->CSacous-1996	-0.027	-0.027	0.013	0.013	0.013	-0.027	-0.026	-0.027
observation->CSacous-1997	-0.912	-0.912	-0.899	-0.899	-0.899	-0.912	-0.912	-0.912
observation->CSacous-1998	-0.054	-0.054	-0.004	-0.004	-0.004	-0.055	-0.054	-0.055
observation->CSacous-1999	-1.025	-1.025	-1.012	-1.012	-1.012	-1.025	-1.025	-1.025
observation->CSacous-2001	-1.217	-1.217	-1.211	-1.211	-1.211	-1.217	-1.217	-1.217
observation->CSacous-2002	-0.297	-0.297	-0.338	-0.338	-0.338	-0.297	-0.297	-0.297
observation->CSacous-2003	-0.845	-0.845	-0.863	-0.863	-0.863	-0.845	-0.845	-0.845
observation->CSacous-2005	-0.929	-0.929	-0.927	-0.927	-0.927	-0.929	-0.929	-0.929
observation->CSacous-2006	-0.939	-0.939	-0.950	-0.950	-0.950	-0.939	-0.939	-0.939
observation->CSacous-2007	-0.623	-0.623	-0.600	-0.600	-0.600	-0.623	-0.623	-0.623
observation->CSacous-2008	-1.094	-1.094	-1.125	-1.125	-1.125	-1.094	-1.094	-1.094
observation->CSacous-2009	-0.185	-0.185	-0.110	-0.110	-0.110	-0.186	-0.185	-0.186
observation->CSacous-2011	-1.021	-1.021	-1.000	-1.000	-1.000	-1.021	-1.021	-1.021
observation->CSacous-2013	-0.892	-0.892	-0.855	-0.855	-0.855	-0.892	-0.892	-0.892
observation->CSacous-2015	-0.190	-0.190	-0.150	-0.150	-0.150	-0.191	-0.190	-0.191
observation->CSacous-2017	-1.020	-1.020	-1.021	-1.021	-1.021	-1.020	-1.020	-1.020
observation->WCacous-1988	-0.588	-0.588	-0.588	-0.588	-0.588	-0.588	-0.588	-0.588
observation->WCacous-1989	-0.183	-0.183	-0.168	-0.168	-0.168	-0.184	-0.183	-0.184
observation->WCacous-1990	-0.332	-0.332	-0.327	-0.327	-0.327	-0.331	-0.332	-0.331
observation->WCacous-1991	-0.425	-0.425	-0.425	-0.425	-0.425	-0.425	-0.425	-0.425
observation->WCacous-1992	-0.744	-0.744	-0.744	-0.744	-0.744	-0.744	-0.744	-0.744
observation->WCacous-1993	-0.369	-0.369	-0.374	-0.374	-0.374	-0.371	-0.369	-0.371
observation->WCacous-1997	-0.054	-0.054	-0.043	-0.043	-0.043	-0.055	-0.054	-0.055
observation->WCacous-2000	-1.265	-1.265	-1.272	-1.272	-1.272	-1.264	-1.265	-1.264
observation->WCacous-2012	-0.906	-0.906	-0.896	-0.896	-0.896	-0.906	-0.906	-0.906
observation->WCacous-2013	-1.079	-1.079	-1.079	-1.079	-1.079	-1.079	-1.079	-1.079
observation->CRsumbio-1992	-1.634	-1.634	-1.647	-1.647	-1.647	-1.634	-1.634	-1.634
observation->CRsumbio-1993	0.040	0.040	0.043	0.043	0.043	0.041	0.040	0.041
observation->CRsumbio-1994	-1.760	-1.760	-1.760	-1.760	-1.760	-1.761	-1.760	-1.761
observation->CRsumbio-1995	-1.425	-1.425	-1.406	-1.406	-1.406	-1.431	-1.425	-1.431
observation->CRsumbio-1996	-1.690	-1.690	-1.699	-1.699	-1.699	-1.691	-1.690	-1.691
observation->CRsumbio-1997	-0.607	-0.607	-0.635	-0.635	-0.635	-0.609	-0.607	-0.609
observation->CRsumbio-1998	-1.203	-1.203	-1.210	-1.210	-1.210	-1.205	-1.203	-1.205
observation->CRsumbio-1999	-0.953	-0.953	-0.919	-0.919	-0.919	-0.950	-0.953	-0.950
observation->CRsumbio-2000	-1.629	-1.629	-1.632	-1.632	-1.632	-1.629	-1.629	-1.629
observation->CRsumbio-2001	-1.773	-1.773	-1.775	-1.775	-1.775	-1.773	-1.773	-1.773
observation->CRsumbio-2002	-1.209	-1.209	-1.206	-1.206	-1.206	-1.205	-1.209	-1.205
observation->CRsumbio-2003	-1.749	-1.749	-1.744	-1.744	-1.744	-1.748	-1.749	-1.748
observation->CRsumbio-2004	-0.818	-0.818	-0.803	-0.803	-0.803	-0.821	-0.818	-0.821
observation->CRsumbio-2005	-1.471	-1.471	-1.477	-1.477	-1.477	-1.470	-1.471	-1.470
observation->CRsumbio-2006	-1.314	-1.314	-1.306	-1.306	-1.306	-1.314	-1.314	-1.314
observation->CRsumbio-2007	-0.727	-0.727	-0.756	-0.756	-0.756	-0.726	-0.727	-0.726
observation->CRsumbio-2008	-0.373	-0.373	-0.402	-0.402	-0.402	-0.376	-0.373	-0.376
observation->CRsumbio-2009	-0.586	-0.586	-0.559	-0.559	-0.559	-0.587	-0.586	-0.587
observation->CRsumbio-2010	-1.349	-1.349	-1.359	-1.359	-1.359	-1.350	-1.349	-1.350
observation->CRsumbio-2011	-1.096	-1.096	-1.105	-1.105	-1.105	-1.094	-1.096	-1.094
observation->CRsumbio-2012	-1.439	-1.439	-1.448	-1.448	-1.448	-1.438	-1.439	-1.438
observation->CRsumbio-2013	-1.494	-1.494	-1.491	-1.491	-1.491	-1.494	-1.494	-1.494
observation->CRsumbio-2014	-1.768	-1.768	-1.770	-1.770	-1.770	-1.768	-1.768	-1.768
observation->CRsumbio-2016	-1.410	-1.410	-1.411	-1.411	-1.411	-1.411	-1.410	-1.411
observation->CRsumbio-2018	-1.552	-1.552	-1.554	-1.554	-1.554	-1.552	-1.552	-1.552
observation->SAsumbio-1992	-0.597	-0.597	-0.588	-0.588	-0.588	-0.596	-0.597	-0.596
observation->SAsumbio-1993	-0.314	-0.314	-0.309	-0.309	-0.309	-0.314	-0.314	-0.314
observation->SAsumbio-1994	0.196	0.196	0.186	0.186	0.186	0.194	0.196	0.194
observation->SAsumbio-2001	-0.835	-0.835	-0.822	-0.822	-0.822	-0.834	-0.835	-0.834
observation->SAsumbio-2002	-0.794	-0.794	-0.777	-0.777	-0.777	-0.794	-0.794	-0.794
observation->SAsumbio-2003	-0.837	-0.837	-0.825	-0.825	-0.825	-0.836	-0.837	-0.836
observation->SAsumbio-2004	0.732	0.732	0.734	0.734	0.734	0.735	0.732	0.735
observation->SAsumbio-2005	-0.258	-0.258	-0.218	-0.218	-0.218	-0.255	-0.258	-0.255
observation->SAsumbio-2006	-0.600	-0.600	-0.558	-0.558	-0.558	-0.598	-0.600	-0.598
observation->SAsumbio-2007	0.636	0.636	0.654	0.654	0.654	0.637	0.636	0.637
observation->SAsumbio-2008	-0.461	-0.461	-0.462	-0.462	-0.462	-0.463	-0.461	-0.463
observation->SAsumbio-2009	-0.585	-0.585	-0.583	-0.583	-0.583	-0.584	-0.585	-0.584
observation->SAsumbio-2010	-0.143	-0.143	-0.147	-0.147	-0.147	-0.146	-0.143	-0.146
observation->SAsumbio-2012	-0.848	-0.848	-0.835	-0.835	-0.835	-0.848	-0.848	-0.848
observation->SAsumbio-2013	-0.797	-0.797	-0.786	-0.786	-0.786	-0.796	-0.797	-0.796
observation->SAsumbio-2015	-0.200	-0.200	-0.189	-0.189	-0.189	-0.201	-0.200	-0.201
observation->SAsumbio-2017	-0.638	-0.638	-0.620	-0.620	-0.620	-0.638	-0.638	-0.638
observation->SAautbio-1992	-1.459	-1.459	-1.450	-1.450	-1.450	-1.460	-1.459	-1.460
observation->SAautbio-1996	-1.233	-1.233	-1.250	-1.250	-1.250	-1.232	-1.233	-1.232
observation->SAautbio-1998	-1.308	-1.308	-1.284	-1.284	-1.284	-1.306	-1.308	-1.306
observation->Espage-1988	19.793	19.793	19.640	19.640	19.640	19.790	19.793	19.790
observation->Espage-1989	15.858	15.858	15.862	15.862	15.862	15.857	15.858	15.857
observation->Espage-1990	21.488	21.488	21.446	21.446	21.446	21.486	21.488	21.486
observation->Espage-1991	20.641	20.641	20.612	20.612	20.612	20.640	20.641	20.640
observation->Espage-1992	24.089	24.089	24.020	24.020	24.020	24.092	24.089	24.092
observation->Espage-1993	19.305	19.305	19.328	19.328	19.328	19.304	19.305	19.304
observation->Espage-1994	20.528	20.528	20.503	20.503	20.503	20.522	20.528	20.522
observation->Espage-1995	22.541	22.541	22.559	22.559	22.559	22.530	22.541	22.530
observation->Espage-1996	18.590	18.590	18.577	18.577	18.577	18.590	18.590	18.590
observation->Espage-1997	20.974	20.974	20.964	20.964	20.964	20.978	20.974	20.978
observation->Espage-1998	20.587	20.587	20.611	20.611	20.611	20.579	20.587	20.579
observation->Espage-1999	22.886	22.886	22.862	22.862	22.862	22.875	22.886	22.875
observation->Espage-2000	23.321	23.321	23.314	23.314	23.314	23.321	23.321	23.321
observation->Espage-2001	20.735	20.735	20.773	20.773	20.773	20.735	20.735	20.735
observation->Espage-2002	26.248	26.248	26.287	26.287	26.287	26.243	26.248	26.243
observation->Espage-2003	19.120	19.120	19.120	19.120	19.120	19.118	19.120	19.118
observation->Espage-2004	22.692	22.692	22.642	22.642	22.642	22.698	22.692	22.698
observation->Espage-2005	26.122	26.122	26.070	26.070	26.070	26.120	26.122	26.120
observation->Espage-2006	23.242	23.242	23.149	23.149	23.149	23.245	23.242	23.245
observation->Espage-2007	25.274	25.274	25.210	25.210	25.210	25.277	25.274	25.277
observation->Espage-2008	22.167	22.167	22.129	22.129	22.129	22.166	22.167	22.166
observation->Espage-2009	18.691	18.691	18.690	18.690	18.690	18.691	18.691	18.691
observation->Espage-2010	21.855	21.855	21.851	21.851	21.851	21.856	21.855	21.856
observation->Espage-2014	20.616	20.616	20.648	20.648	20.648	20.614	20.616	20.614
observation->Espage-2015	21.823	21.823	21.870	21.870	21.870	21.820	21.823	21.820
observation->Espage-2016	21.204	21.204	21.204	21.204	21.204	21.203	21.204	21.203
observation->Espage-2017	21.575	21.575	21.563	21.563	21.563	21.578	21.575	21.578
observation->Wspage-1988	15.724	15.724	15.753	15.753	15.753	15.729	15.724	15.729
observation->Wspage-1989	11.555	11.555	11.566	11.566	11.566	11.558	11.555	11.558
observation->Wspage-1990	11.752	11.752	11.790	11.790	11.790	11.750	11.752	11.750
observation->Wspage-1991	13.036	13.036	13.051	13.051	13.051	13.037	13.036	13.037
observation->Wspage-1992	10.178	10.178	10.170	10.170	10.170	10.179	10.178	10.179
observation->Wspage-1993	10.569	10.569	10.579	10.579	10.579	10.571	10.569	10.571
observation->Wspage-1994	9.918	9.918	9.924	9.924	9.924	9.918	9.918	9.918
observation->Wspage-1995	13.403	13.403	13.396	13.396	13.396	13.399	13.403	13.399
observation->Wspage-1996	11.840	11.840	11.844	11.844	11.844	11.841	11.840	11.841
observation->Wspage-1997	11.230	11.230	11.243	11.243	11.243	11.233	11.230	11.233
observation->Wspage-1998	11.761	11.761	11.762	11.762	11.762	11.761	11.761	11.761
observation->Wspage-1999	11.975	11.975	11.981	11.981	11.981	11.976	11.975	11.976
observation->Wspage-2000	11.256	11.256	11.260	11.260	11.260	11.256	11.256	11.256
observation->Wspage-2001	12.179	12.179	12.201	12.201	12.201	12.181	12.179	12.181
observation->Wspage-2002	9.731	9.731	9.745	9.745	9.745	9.732	9.731	9.732
observation->Wspage-2003	9.555	9.555	9.556	9.556	9.556	9.555	9.555	9.555
observation->Wspage-2004	14.340	14.340	14.304	14.304	14.304	14.342	14.340	14.342
observation->Wspage-2005	14.932	14.932	14.977	14.977	14.977	14.934	14.932	14.934
observation->Wspage-2006	13.817	13.817	13.872	13.872	13.872	13.817	13.817	13.817
observation->Wspage-2007	11.498	11.498	11.516	11.516	11.516	11.500	11.498	11.500
observation->Wspage-2008	12.195	12.195	12.194	12.194	12.194	12.196	12.195	12.196
observation->Wspage-2009	12.631	12.631	12.594	12.594	12.594	12.635	12.631	12.635
observation->Wspage-2010	11.316	11.316	11.299	11.299	11.299	11.317	11.316	11.317
observation->Wspage-2011	11.154	11.154	11.137	11.137	11.137	11.155	11.154	11.155
observation->Wspage-2012	11.867	11.867	11.860	11.860	11.860	11.866	11.867	11.866
observation->Wspage-2013	11.041	11.041	11.065	11.065	11.065	11.043	11.041	11.043
observation->Wspage-2014	12.944	12.944	12.941	12.941	12.941	12.944	12.944	12.944
observation->Wspage-2015	13.134	13.134	13.101	13.101	13.101	13.136	13.134	13.136
observation->Wspage-2016	14.272	14.272	14.273	14.273	14.273	14.268	14.272	14.268
observation->Wspage-2017	13.745	13.745	13.797	13.797	13.797	13.746	13.745	13.746
observation->EnspOLF-1992	4.397	4.397	4.388	4.388	4.388	4.396	4.397	4.396
observation->EnspOLF-1994	6.647	6.647	6.678	6.678	6.678	6.645	6.647	6.645
observation->EnspOLF-1996	7.897	7.897	7.906	7.906	7.906	7.899	7.897	7.899
observation->EnspOLF-1998	5.301	5.301	5.303	5.303	5.303	5.301	5.301	5.301
observation->Enspage-1999	14.332	14.332	14.287	14.287	14.287	14.331	14.332	14.331
observation->Enspage-2000	13.975	13.975	13.960	13.960	13.960	13.973	13.975	13.973
observation->Enspage-2001	13.979	13.979	13.929	13.929	13.929	13.959	13.979	13.959
observation->Enspage-2002	12.081	12.081	12.078	12.078	12.078	12.087	12.081	12.087
observation->Enspage-2003	9.700	9.700	9.706	9.706	9.706	9.702	9.700	9.702
observation->Enspage-2004	12.966	12.966	12.986	12.986	12.986	12.972	12.966	12.972
observation->Enspage-2005	11.012	11.012	11.009	11.009	11.009	11.009	11.012	11.009
observation->Enspage-2006	12.741	12.741	12.712	12.712	12.712	12.744	12.741	12.744
observation->Enspage-2007	11.061	11.061	11.052	11.052	11.052	11.060	11.061	11.060
observation->Enspage-2008	12.104	12.104	12.101	12.101	12.101	12.100	12.104	12.100
observation->Enspage-2009	10.056	10.056	10.055	10.055	10.055	10.055	10.056	10.055
observation->Enspage-2010	17.581	17.581	17.627	17.627	17.627	17.576	17.581	17.576
observation->Enspage-2011	13.399	13.399	13.412	13.412	13.412	13.402	13.399	13.402
observation->Enspage-2012	13.149	13.149	13.134	13.134	13.134	13.148	13.149	13.148
observation->Enspage-2013	16.694	16.694	16.659	16.659	16.659	16.691	16.694	16.691
observation->Enspage-2014	13.869	13.869	13.870	13.870	13.870	13.868	13.869	13.868
observation->Enspage-2015	12.760	12.760	12.776	12.776	12.776	12.764	12.760	12.764
observation->Enspage-2016	19.224	19.224	19.203	19.203	19.203	19.222	19.224	19.222
observation->Enspage-2017	15.562	15.562	15.511	15.511	15.511	15.552	15.562	15.552
observation->WnspOLF-1992	10.122	10.122	10.129	10.129	10.129	10.124	10.122	10.124
observation->WnspOLF-1993	9.045	9.045	8.991	8.991	8.991	9.047	9.045	9.047
observation->WnspOLF-1994	15.930	15.930	15.893	15.893	15.893	15.931	15.930	15.931
observation->WnspOLF-1996	9.788	9.788	9.752	9.752	9.752	9.784	9.788	9.784
observation->WnspOLF-1999	11.554	11.553	11.593	11.593	11.593	11.553	11.553	11.553
observation->WnspOLF-2000	13.812	13.812	13.892	13.892	13.892	13.817	13.812	13.817
observation->Wnspage-2001	8.032	8.032	7.994	7.994	7.994	8.036	8.032	8.036
observation->Wnspage-2002	8.715	8.715	8.701	8.701	8.701	8.714	8.715	8.714
observation->Wnspage-2003	10.473	10.473	10.507	10.507	10.507	10.473	10.473	10.473
observation->Wnspage-2004	7.155	7.155	7.140	7.140	7.140	7.154	7.155	7.154
observation->Wnspage-2006	9.589	9.589	9.551	9.551	9.551	9.590	9.589	9.590
observation->Wnspage-2007	10.861	10.861	10.822	10.822	10.822	10.860	10.861	10.860
observation->Wnspage-2008	12.425	12.425	12.435	12.435	12.435	12.422	12.425	12.422
observation->Wnspage-2009	14.716	14.716	14.790	14.790	14.790	14.719	14.716	14.719
observation->Wnspage-2010	11.405	11.405	11.370	11.370	11.370	11.405	11.405	11.405
observation->Wnspage-2011	11.267	11.267	11.275	11.275	11.275	11.265	11.267	11.265
observation->Wnspage-2012	10.454	10.454	10.465	10.465	10.465	10.453	10.454	10.453
observation->Wnspage-2013	13.633	13.633	13.634	13.634	13.634	13.634	13.633	13.634
observation->Wnspage-2014	12.608	12.608	12.597	12.597	12.597	12.609	12.608	12.609
observation->Wnspage-2016	15.687	15.687	15.722	15.722	15.722	15.683	15.687	15.683
observation->CRsumage-1992	15.584	15.584	15.566	15.566	15.566	15.570	15.584	15.570
observation->CRsumage-1993	10.616	10.616	10.624	10.624	10.624	10.613	10.616	10.613
observation->CRsumage-1994	18.170	18.170	18.130	18.130	18.130	18.174	18.170	18.174
observation->CRsumage-1995	14.285	14.285	14.242	14.242	14.242	14.287	14.285	14.287
observation->CRsumage-1996	11.567	11.567	11.607	11.607	11.607	11.566	11.567	11.566
observation->CRsumage-1997	15.754	15.754	15.688	15.688	15.688	15.750	15.754	15.750
observation->CRsumage-1998	14.690	14.690	14.690	14.690	14.690	14.686	14.690	14.686
observation->CRsumage-1999	12.061	12.061	12.084	12.084	12.084	12.061	12.061	12.061
observation->CRsumage-2000	14.323	14.323	14.283	14.283	14.283	14.326	14.323	14.326
observation->CRsumage-2001	19.659	19.659	19.520	19.520	19.520	19.651	19.659	19.651
observation->CRsumage-2002	10.969	10.969	10.960	10.960	10.960	10.971	10.969	10.971
observation->CRsumage-2003	11.251	11.251	11.210	11.210	11.210	11.254	11.251	11.254
observation->CRsumage-2004	9.553	9.553	9.561	9.561	9.561	9.556	9.553	9.556
observation->CRsumage-2005	12.753	12.753	12.654	12.654	12.654	12.749	12.753	12.749
observation->CRsumage-2006	10.316	10.316	10.317	10.317	10.317	10.317	10.316	10.317
observation->CRsumage-2007	13.562	13.562	13.504	13.504	13.504	13.561	13.562	13.561
observation->CRsumage-2008	11.661	11.661	11.639	11.639	11.639	11.665	11.661	11.665
observation->CRsumage-2009	12.006	12.006	11.965	11.965	11.965	12.002	12.006	12.002
observation->CRsumage-2010	11.048	11.048	11.055	11.055	11.055	11.052	11.048	11.052
observation->CRsumage-2011	12.579	12.579	12.571	12.571	12.571	12.577	12.579	12.577
observation->CRsumage-2012	17.228	17.228	17.141	17.141	17.141	17.230	17.228	17.230
observation->CRsumage-2013	11.843	11.843	11.822	11.822	11.822	11.845	11.843	11.845
observation->CRsumage-2014	11.286	11.286	11.271	11.271	11.271	11.288	11.286	11.288
observation->CRsumage-2016	9.866	9.866	9.847	9.847	9.847	9.867	9.866	9.867
observation->CRsumage-2018	11.931	11.931	11.895	11.895	11.895	11.935	11.931	11.935
observation->SAsumage-1992	12.246	12.246	12.269	12.269	12.269	12.241	12.246	12.241
observation->SAsumage-1993	12.470	12.470	12.502	12.502	12.502	12.483	12.470	12.483
observation->SAsumage-1994	10.811	10.811	10.818	10.818	10.818	10.808	10.811	10.808
observation->SAsumage-2001	12.749	12.749	12.839	12.839	12.839	12.762	12.749	12.762
observation->SAsumage-2002	12.209	12.209	12.254	12.254	12.254	12.216	12.209	12.216
observation->SAsumage-2003	13.386	13.386	13.386	13.386	13.386	13.388	13.386	13.388
observation->SAsumage-2004	11.067	11.067	11.005	11.005	11.005	11.064	11.067	11.064
observation->SAsumage-2005	15.278	15.278	15.386	15.386	15.386	15.280	15.278	15.280
observation->SAsumage-2006	14.112	14.112	14.078	14.078	14.078	14.110	14.112	14.110
observation->SAsumage-2007	10.649	10.649	10.639	10.639	10.639	10.649	10.649	10.649
observation->SAsumage-2008	13.771	13.771	13.836	13.836	13.836	13.766	13.771	13.766
observation->SAsumage-2009	15.513	15.513	15.530	15.530	15.530	15.520	15.513	15.520
observation->SAsumage-2010	15.081	15.081	15.130	15.130	15.130	15.082	15.081	15.082
observation->SAsumage-2012	13.437	13.437	13.479	13.479	13.479	13.439	13.437	13.439
observation->SAsumage-2013	11.954	11.954	11.982	11.982	11.982	11.956	11.954	11.956
observation->SAsumage-2015	13.522	13.522	13.540	13.540	13.540	13.524	13.522	13.524
observation->SAsumage-2017	12.492	12.492	12.478	12.478	12.478	12.487	12.492	12.487
observation->SAautage-1992	11.809	11.809	11.857	11.857	11.857	11.819	11.809	11.819
observation->SAautage-1996	10.449	10.449	10.426	10.426	10.426	10.450	10.449	10.450
observation->SAautage-1998	12.809	12.809	12.835	12.835	12.835	12.810	12.809	12.810
observation->pspawn_1993	-6.017	-6.017	-6.015	-6.015	-6.015	-6.016	-6.017	-6.016
observation->pspawn-1992	-4.848	-4.848	-4.829	-4.829	-4.829	-4.852	-4.848	-4.852
observation->pspawn-1998	-8.284	-8.284	-8.300	-8.300	-8.300	-8.291	-8.284	-8.291
prior->CSacousq->catchability[CSacous].q	-0.849	-0.849	-0.839	-0.839	-0.839	-0.847	-0.849	-0.847
prior->WCacousq->catchability[WCacous].q	-1.162	-1.162	-1.202	-1.202	-1.202	-1.163	-1.162	-1.163
prior->CRsumq->catchability[CRsum].q	-2.155	-2.155	-2.207	-2.207	-2.207	-2.153	-2.155	-2.153
prior->SAsumq->catchability[SAsum].q	-1.762	-1.762	-1.557	-1.557	-1.557	-1.760	-1.762	-1.760
prior->SAautq->catchability[SAaut].q	-1.913	-1.913	-1.762	-1.762	-1.762	-1.911	-1.913	-1.911
prior->CR_process_error->observation[CRsumbio].process_error	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->SA_process_error->observation[SAsumbio].process_error	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->B0_E_with_total_log_b0_prior->process[recruit_E].b0	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->B0_W_with_proportion_prior->process[recruit_W].b0	12.544	12.544	12.555	12.555	12.555	12.545	12.544	12.545
prior->M_all->process[Instant_mortality].m{west.sa}	-1.085	-1.085	-1.217	-1.217	-1.217	-1.083	-1.085	-1.083
prior->Wspsl_shift_param->time_varying[shifted_mu].a	0.420	0.420	0.378	0.378	0.378	0.422	0.420	0.422
prior->YCS_E->process[recruit_E].ycs_values{1975}	-0.624	-0.624	-0.623	-0.623	-0.623	-0.624	-0.624	-0.624
prior->YCS_E->process[recruit_E].ycs_values{1976}	-0.316	-0.316	-0.319	-0.319	-0.319	-0.314	-0.316	-0.314
prior->YCS_E->process[recruit_E].ycs_values{1977}	-0.227	-0.227	-0.238	-0.238	-0.238	-0.225	-0.227	-0.225
prior->YCS_E->process[recruit_E].ycs_values{1978}	0.654	0.654	0.615	0.615	0.615	0.656	0.654	0.656
prior->YCS_E->process[recruit_E].ycs_values{1979}	0.084	0.084	0.062	0.062	0.062	0.086	0.084	0.086
prior->YCS_E->process[recruit_E].ycs_values{1980}	-0.630	-0.630	-0.627	-0.627	-0.627	-0.630	-0.630	-0.630
prior->YCS_E->process[recruit_E].ycs_values{1981}	-0.619	-0.619	-0.623	-0.623	-0.623	-0.619	-0.619	-0.619
prior->YCS_E->process[recruit_E].ycs_values{1982}	-0.550	-0.550	-0.542	-0.542	-0.542	-0.551	-0.550	-0.551
prior->YCS_E->process[recruit_E].ycs_values{1983}	-0.627	-0.627	-0.630	-0.630	-0.630	-0.627	-0.627	-0.627
prior->YCS_E->process[recruit_E].ycs_values{1984}	-0.591	-0.591	-0.596	-0.596	-0.596	-0.591	-0.591	-0.591
prior->YCS_E->process[recruit_E].ycs_values{1985}	-0.641	-0.641	-0.642	-0.642	-0.642	-0.641	-0.641	-0.641
prior->YCS_E->process[recruit_E].ycs_values{1986}	-0.408	-0.408	-0.400	-0.400	-0.400	-0.408	-0.408	-0.408
prior->YCS_E->process[recruit_E].ycs_values{1987}	0.142	0.142	0.135	0.135	0.135	0.142	0.142	0.142
prior->YCS_E->process[recruit_E].ycs_values{1988}	0.026	0.026	0.019	0.019	0.019	0.025	0.026	0.025
prior->YCS_E->process[recruit_E].ycs_values{1989}	-0.631	-0.631	-0.632	-0.632	-0.632	-0.631	-0.631	-0.631
prior->YCS_E->process[recruit_E].ycs_values{1990}	0.159	0.159	0.158	0.158	0.158	0.159	0.159	0.159
prior->YCS_E->process[recruit_E].ycs_values{1991}	-0.643	-0.643	-0.643	-0.643	-0.643	-0.643	-0.643	-0.643
prior->YCS_E->process[recruit_E].ycs_values{1992}	-0.643	-0.643	-0.643	-0.643	-0.643	-0.643	-0.643	-0.643
prior->YCS_E->process[recruit_E].ycs_values{1993}	-0.643	-0.643	-0.643	-0.643	-0.643	-0.643	-0.643	-0.643
prior->YCS_E->process[recruit_E].ycs_values{1994}	-0.530	-0.530	-0.525	-0.525	-0.525	-0.531	-0.530	-0.531
prior->YCS_E->process[recruit_E].ycs_values{1995}	-0.534	-0.534	-0.538	-0.538	-0.538	-0.534	-0.534	-0.534
prior->YCS_E->process[recruit_E].ycs_values{1996}	-0.574	-0.574	-0.577	-0.577	-0.577	-0.573	-0.574	-0.573
prior->YCS_E->process[recruit_E].ycs_values{1997}	-0.623	-0.623	-0.622	-0.622	-0.622	-0.623	-0.623	-0.623
prior->YCS_E->process[recruit_E].ycs_values{1998}	-0.512	-0.512	-0.513	-0.513	-0.513	-0.511	-0.512	-0.511
prior->YCS_E->process[recruit_E].ycs_values{1999}	2.014	2.014	2.014	2.014	2.014	2.014	2.014	2.014
prior->YCS_E->process[recruit_E].ycs_values{2000}	-0.616	-0.616	-0.614	-0.614	-0.614	-0.616	-0.616	-0.616
prior->YCS_E->process[recruit_E].ycs_values{2001}	-0.065	-0.065	-0.071	-0.071	-0.071	-0.065	-0.065	-0.065
prior->YCS_E->process[recruit_E].ycs_values{2002}	-0.543	-0.543	-0.545	-0.545	-0.545	-0.542	-0.543	-0.542
prior->YCS_E->process[recruit_E].ycs_values{2003}	-0.586	-0.586	-0.585	-0.585	-0.585	-0.586	-0.586	-0.586
prior->YCS_E->process[recruit_E].ycs_values{2004}	-0.568	-0.568	-0.568	-0.568	-0.568	-0.568	-0.568	-0.568
prior->YCS_E->process[recruit_E].ycs_values{2005}	-0.579	-0.579	-0.578	-0.578	-0.578	-0.579	-0.579	-0.579
prior->YCS_E->process[recruit_E].ycs_values{2006}	-0.483	-0.483	-0.482	-0.482	-0.482	-0.483	-0.483	-0.483
prior->YCS_E->process[recruit_E].ycs_values{2007}	-0.567	-0.567	-0.566	-0.566	-0.566	-0.567	-0.567	-0.567
prior->YCS_E->process[recruit_E].ycs_values{2008}	-0.643	-0.643	-0.643	-0.643	-0.643	-0.643	-0.643	-0.643
prior->YCS_E->process[recruit_E].ycs_values{2009}	-0.561	-0.561	-0.562	-0.562	-0.562	-0.561	-0.561	-0.561
prior->YCS_E->process[recruit_E].ycs_values{2010}	-0.031	-0.031	-0.046	-0.046	-0.046	-0.031	-0.031	-0.031
prior->YCS_E->process[recruit_E].ycs_values{2011}	-0.408	-0.408	-0.408	-0.408	-0.408	-0.408	-0.408	-0.408
prior->YCS_E->process[recruit_E].ycs_values{2012}	-0.019	-0.019	-0.023	-0.023	-0.023	-0.019	-0.019	-0.019
prior->YCS_E->process[recruit_E].ycs_values{2013}	-0.238	-0.238	-0.242	-0.242	-0.242	-0.238	-0.238	-0.238
prior->YCS_E->process[recruit_E].ycs_values{2014}	-0.317	-0.317	-0.314	-0.314	-0.314	-0.317	-0.317	-0.317
prior->YCS_E->process[recruit_E].ycs_values{2015}	-0.279	-0.279	-0.302	-0.302	-0.302	-0.284	-0.279	-0.284
prior->YCS_E->process[recruit_E].ycs_values{2016}	0.363	0.363	0.373	0.373	0.373	0.364	0.363	0.364
prior->YCS_W->process[recruit_W].ycs_values{1975}	-0.616	-0.616	-0.617	-0.617	-0.617	-0.616	-0.616	-0.616
prior->YCS_W->process[recruit_W].ycs_values{1976}	-0.195	-0.195	-0.184	-0.184	-0.184	-0.195	-0.195	-0.195
prior->YCS_W->process[recruit_W].ycs_values{1977}	-0.376	-0.376	-0.396	-0.396	-0.396	-0.376	-0.376	-0.376
prior->YCS_W->process[recruit_W].ycs_values{1978}	-0.396	-0.396	-0.417	-0.417	-0.417	-0.397	-0.396	-0.397
prior->YCS_W->process[recruit_W].ycs_values{1979}	-0.607	-0.607	-0.612	-0.612	-0.612	-0.607	-0.607	-0.607
prior->YCS_W->process[recruit_W].ycs_values{1980}	-0.567	-0.567	-0.573	-0.573	-0.573	-0.568	-0.567	-0.568
prior->YCS_W->process[recruit_W].ycs_values{1981}	-0.502	-0.502	-0.508	-0.508	-0.508	-0.502	-0.502	-0.502
prior->YCS_W->process[recruit_W].ycs_values{1982}	-0.606	-0.606	-0.607	-0.607	-0.607	-0.606	-0.606	-0.606
prior->YCS_W->process[recruit_W].ycs_values{1983}	-0.109	-0.109	-0.111	-0.111	-0.111	-0.108	-0.109	-0.108
prior->YCS_W->process[recruit_W].ycs_values{1984}	-0.163	-0.163	-0.163	-0.163	-0.163	-0.161	-0.163	-0.161
prior->YCS_W->process[recruit_W].ycs_values{1985}	-0.619	-0.619	-0.620	-0.620	-0.620	-0.619	-0.619	-0.619
prior->YCS_W->process[recruit_W].ycs_values{1986}	-0.098	-0.098	-0.098	-0.098	-0.098	-0.097	-0.098	-0.097
prior->YCS_W->process[recruit_W].ycs_values{1987}	0.788	0.788	0.782	0.782	0.782	0.789	0.788	0.789
prior->YCS_W->process[recruit_W].ycs_values{1988}	-0.252	-0.252	-0.255	-0.255	-0.255	-0.251	-0.252	-0.251
prior->YCS_W->process[recruit_W].ycs_values{1989}	1.207	1.207	1.211	1.211	1.211	1.207	1.207	1.207
prior->YCS_W->process[recruit_W].ycs_values{1990}	1.197	1.197	1.204	1.204	1.204	1.198	1.197	1.198
prior->YCS_W->process[recruit_W].ycs_values{1991}	-0.081	-0.081	-0.080	-0.080	-0.080	-0.081	-0.081	-0.081
prior->YCS_W->process[recruit_W].ycs_values{1992}	0.480	0.480	0.480	0.480	0.480	0.480	0.480	0.480
prior->YCS_W->process[recruit_W].ycs_values{1993}	-0.643	-0.643	-0.643	-0.643	-0.643	-0.643	-0.643	-0.643
prior->YCS_W->process[recruit_W].ycs_values{1994}	0.014	0.014	0.020	0.020	0.020	0.014	0.014	0.014
prior->YCS_W->process[recruit_W].ycs_values{1995}	-0.410	-0.410	-0.413	-0.413	-0.413	-0.409	-0.410	-0.409
prior->YCS_W->process[recruit_W].ycs_values{1996}	-0.301	-0.301	-0.306	-0.306	-0.306	-0.301	-0.301	-0.301
prior->YCS_W->process[recruit_W].ycs_values{1997}	-0.466	-0.466	-0.471	-0.471	-0.471	-0.467	-0.466	-0.467
prior->YCS_W->process[recruit_W].ycs_values{1998}	-0.322	-0.322	-0.334	-0.334	-0.334	-0.323	-0.322	-0.323
prior->YCS_W->process[recruit_W].ycs_values{1999}	2.014	2.014	2.014	2.014	2.014	2.014	2.014	2.014
prior->YCS_W->process[recruit_W].ycs_values{2000}	-0.643	-0.643	-0.643	-0.643	-0.643	-0.643	-0.643	-0.643
prior->YCS_W->process[recruit_W].ycs_values{2001}	0.856	0.856	0.846	0.846	0.846	0.855	0.856	0.855
prior->YCS_W->process[recruit_W].ycs_values{2002}	-0.222	-0.222	-0.222	-0.222	-0.222	-0.222	-0.222	-0.222
prior->YCS_W->process[recruit_W].ycs_values{2003}	-0.612	-0.612	-0.612	-0.612	-0.612	-0.612	-0.612	-0.612
prior->YCS_W->process[recruit_W].ycs_values{2004}	-0.570	-0.570	-0.571	-0.571	-0.571	-0.570	-0.570	-0.570
prior->YCS_W->process[recruit_W].ycs_values{2005}	-0.574	-0.574	-0.576	-0.576	-0.576	-0.574	-0.574	-0.574
prior->YCS_W->process[recruit_W].ycs_values{2006}	-0.280	-0.280	-0.279	-0.279	-0.279	-0.280	-0.280	-0.280
prior->YCS_W->process[recruit_W].ycs_values{2007}	-0.438	-0.438	-0.436	-0.436	-0.436	-0.438	-0.438	-0.438
prior->YCS_W->process[recruit_W].ycs_values{2008}	-0.464	-0.464	-0.463	-0.463	-0.463	-0.464	-0.464	-0.464
prior->YCS_W->process[recruit_W].ycs_values{2009}	-0.514	-0.514	-0.508	-0.508	-0.508	-0.514	-0.514	-0.514
prior->YCS_W->process[recruit_W].ycs_values{2010}	0.071	0.071	0.078	0.078	0.078	0.070	0.071	0.070
prior->YCS_W->process[recruit_W].ycs_values{2011}	0.031	0.031	0.043	0.043	0.043	0.030	0.031	0.030
prior->YCS_W->process[recruit_W].ycs_values{2012}	-0.050	-0.050	-0.059	-0.059	-0.059	-0.049	-0.050	-0.049
prior->YCS_W->process[recruit_W].ycs_values{2013}	-0.489	-0.489	-0.490	-0.490	-0.490	-0.488	-0.489	-0.488
prior->YCS_W->process[recruit_W].ycs_values{2014}	1.730	1.730	1.742	1.742	1.742	1.727	1.730	1.727
prior->YCS_W->process[recruit_W].ycs_values{2015}	1.681	1.681	1.687	1.687	1.687	1.684	1.681	1.684
prior->YCS_W->process[recruit_W].ycs_values{2016}	0.363	0.363	0.373	0.373	0.373	0.364	0.363	0.364
prior->sel_Whome->selectivity[sel_Whome].v{1}	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->sel_Whome->selectivity[sel_Whome].v{2}	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->sel_Whome->selectivity[sel_Whome].v{3}	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->sel_Whome->selectivity[sel_Whome].v{4}	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->sel_Whome->selectivity[sel_Whome].v{5}	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->sel_Whome->selectivity[sel_Whome].v{6}	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->sel_Whome->selectivity[sel_Whome].v{7}	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->sel_Espmg_male->selectivity[sel_Espmg].v{1}	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->sel_Espmg_male->selectivity[sel_Espmg].v{2}	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->sel_Espmg_male->selectivity[sel_Espmg].v{3}	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->sel_Espmg_male->selectivity[sel_Espmg].v{4}	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->sel_Espmg_male->selectivity[sel_Espmg].v{5}	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->sel_Espmg_male->selectivity[sel_Espmg].v{6}	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->sel_Espmg_male->selectivity[sel_Espmg].v{7}	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->sel_Espmg_male->selectivity[sel_Espmg].v{8}	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->sel_Wspmg_male->selectivity[sel_Wspmg].v{1}	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->sel_Wspmg_male->selectivity[sel_Wspmg].v{2}	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->sel_Wspmg_male->selectivity[sel_Wspmg].v{3}	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->sel_Wspmg_male->selectivity[sel_Wspmg].v{4}	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->sel_Wspmg_male->selectivity[sel_Wspmg].v{5}	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->sel_Wspmg_male->selectivity[sel_Wspmg].v{6}	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->sel_Wspmg_male->selectivity[sel_Wspmg].v{7}	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->sel_Wspmg_male->selectivity[sel_Wspmg].v{8}	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->Enspsl_mu->selectivity[Enspsl].mu	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->Enspsl_s_l->selectivity[Enspsl].sigma_l	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->Enspsl_s_r->selectivity[Enspsl].sigma_r	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->Wnspsl_mu->selectivity[Wnspsl].mu	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->Wnspsl_s_l->selectivity[Wnspsl].sigma_l	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->Wnspsl_s_r->selectivity[Wnspsl].sigma_r	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->Espsl_mu->selectivity[Espsl].mu	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->Espsl_s_l->selectivity[Espsl].sigma_l	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->Espsl_s_r->selectivity[Espsl].sigma_r	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->CRsl_mu->selectivity[CRsl].mu	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->CRsl_s_l->selectivity[CRsl].sigma_l	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->CRsl_s_r->selectivity[CRsl].sigma_r	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->SAsl_mu->selectivity[SAsl].mu	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->SAsl_s_l->selectivity[SAsl].sigma_l	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
prior->SAsl_s_r->selectivity[SAsl].sigma_r	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
additional_prior->YCS.eq.16	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
additional_prior->sp.migr	0.009	0.009	0.013	0.013	0.013	0.009	0.009	0.009
jacobian->log_sum_b0	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
total_score	1946.810	1946.810	1946.540	1946.540	1946.540	1946.800	1946.810	1946.800

## [1] "CASAL base model convergence information"

## [1] "fmm: have converged: t = 8.24015e-007 f = 1946.54"                                                        
## [2] "Successful convergence in optimise"                                                                       
## [3] "Minimiser achieved convergence after 599 quasi-Newton iterations using 669 objective function evaluations"

## [1] ""

## [1] "CASAL sensitivity 1 model convergence information"

## [1] "fmm: step size too small. Indicates successful convergence (though this is not the textbook ideal convergence situation)"
## [2] "Successful convergence in optimise"                                                                                      
## [3] "Minimiser achieved convergence after 665 quasi-Newton iterations using 765 objective function evaluations"

## [1] ""
## [1] "Casal2 betadiff_casal_flags_on model convergence information"
## [1] "fmm: have converged: t = 4.80834e-07 f = 1946.81"
## [2] "Successful convergence in optimise"              
## [1] ""
## [1] "Casal2 betadiff_casal_flags_off model convergence information"
## [1] "fmm: have converged: t = 4.25092e-07 f = 1946.81"
## [2] "Successful convergence in optimise"              
## [1] ""
## [1] "Casal2 betadiff_casal_flags_on_low_tol model convergence information"
## [1] "fmm: step size too small. Indicates successful convergence (though this is not the textbook ideal convergence situation)"
## [2] "Successful convergence in optimise"                                                                                      
## [1] ""
## [1] "Casal2 cppad_casal_flags_on model convergence information"
##  [1] "Number of nonzeros in equality constraint Jacobian...:        0"
##  [2] "Number of nonzeros in inequality constraint Jacobian.:      133"
##  [3] "Number of nonzeros in Lagrangian Hessian.............:     8911"
##  [4] "Number of Iterations....: 56"                                   
##  [5] "Number of objective function evaluations             = 91"      
##  [6] "Number of objective gradient evaluations             = 57"      
##  [7] "Number of equality constraint evaluations            = 0"       
##  [8] "Number of inequality constraint evaluations          = 91"      
##  [9] "Number of equality constraint Jacobian evaluations   = 0"       
## [10] "Number of inequality constraint Jacobian evaluations = 57"      
## [11] "Number of Lagrangian Hessian evaluations             = 56"      
## [12] "EXIT: Optimal Solution Found."                                  
## [1] ""
## [1] "Casal2 cppad_casal_flags_off model convergence information"
##  [1] "Number of nonzeros in equality constraint Jacobian...:        0"
##  [2] "Number of nonzeros in inequality constraint Jacobian.:      133"
##  [3] "Number of nonzeros in Lagrangian Hessian.............:     8911"
##  [4] "Number of Iterations....: 56"                                   
##  [5] "Number of objective function evaluations             = 95"      
##  [6] "Number of objective gradient evaluations             = 57"      
##  [7] "Number of equality constraint evaluations            = 0"       
##  [8] "Number of inequality constraint evaluations          = 95"      
##  [9] "Number of equality constraint Jacobian evaluations   = 0"       
## [10] "Number of inequality constraint Jacobian evaluations = 57"      
## [11] "Number of Lagrangian Hessian evaluations             = 56"      
## [12] "EXIT: Optimal Solution Found."                                  
## [1] ""
## [1] "Casal2 adolc_casal_flags_on model convergence information"
## character(0)
## [1] ""
## [1] "Casal2 adolc_casal_flags_off model convergence information"
## character(0)
## [1] ""
## [1] "Casal2 adolc_casal_flags_on_low_tol model convergence information"
## character(0)

## [1] "CASAL model warnings"

##                  parameter estimate lower.bound upper.bound
## 1   recruitment[E].YCS[25]     0.06        0.06         8.6
## 2   recruitment[W].YCS[25]     0.06        0.06         8.6
## 3 selectivity[CRsl].all[1]        1           1          17
## 4 selectivity[CRsl].all[2]        1           1          50

## [1] ""

## [1] "CASAL sensitivity 1 model warnings"

##                  parameter estimate lower.bound upper.bound
## 1   recruitment[E].YCS[25]     0.06        0.06         8.6
## 2   recruitment[W].YCS[25]     0.06        0.06         8.6
## 3 selectivity[CRsl].all[1]        1           1          17
## 4 selectivity[CRsl].all[2]        1           1          50

## [1] ""
## [1] "Casal2 betadiff_casal_flags_on model warnings"
## $warnings_found
## [1] 10
## 
## $warning_0
## [1] "Estimates were removed because of matching lower and upper bounds. Originally had 134 estimates, now have 133"
## 
## $warning_1
## [1] "estimated parameter 'process[recruit_E].b0' was within 0.001 of upper bound 16.2"
## 
## $warning_2
## [1] "estimated parameter 'process[recruit_W].b0' was within 0.001 of upper bound 0.59"
## 
## $warning_3
## [1] "estimated parameter 'process[recruit_E].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_4
## [1] "estimated parameter 'process[recruit_W].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_5
## [1] "estimated parameter 'selectivity[sel_Whome].v{7}' was within 0.001 of upper bound 1"
## 
## $warning_6
## [1] "estimated parameter 'selectivity[Enspsl].sigma_r' was within 0.001 of upper bound 50"
## 
## $warning_7
## [1] "estimated parameter 'selectivity[Wnspsl].sigma_r' was within 0.001 of upper bound 50"
## 
## $warning_8
## [1] "estimated parameter 'selectivity[CRsl].mu' was within 0.001 of lower bound 1"
## 
## $warning_9
## [1] "estimated parameter 'selectivity[SAsl].sigma_r' was within 0.001 of lower bound 1"
## 
## $type
## [1] "warnings"
## 
## [1] ""
## [1] "Casal2 betadiff_casal_flags_off model warnings"
## $warnings_found
## [1] 10
## 
## $warning_0
## [1] "Estimates were removed because of matching lower and upper bounds. Originally had 134 estimates, now have 133"
## 
## $warning_1
## [1] "estimated parameter 'process[recruit_E].b0' was within 0.001 of upper bound 16.2"
## 
## $warning_2
## [1] "estimated parameter 'process[recruit_W].b0' was within 0.001 of upper bound 0.59"
## 
## $warning_3
## [1] "estimated parameter 'process[recruit_E].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_4
## [1] "estimated parameter 'process[recruit_W].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_5
## [1] "estimated parameter 'selectivity[sel_Whome].v{7}' was within 0.001 of upper bound 1"
## 
## $warning_6
## [1] "estimated parameter 'selectivity[Enspsl].sigma_r' was within 0.001 of upper bound 50"
## 
## $warning_7
## [1] "estimated parameter 'selectivity[Wnspsl].sigma_r' was within 0.001 of upper bound 50"
## 
## $warning_8
## [1] "estimated parameter 'selectivity[CRsl].mu' was within 0.001 of lower bound 1"
## 
## $warning_9
## [1] "estimated parameter 'selectivity[SAsl].sigma_r' was within 0.001 of lower bound 1"
## 
## $type
## [1] "warnings"
## 
## [1] ""
## [1] "Casal2 betadiff_casal_flags_on_low_tol model warnings"
## $warnings_found
## [1] 6
## 
## $warning_0
## [1] "Estimates were removed because of matching lower and upper bounds. Originally had 134 estimates, now have 133"
## 
## $warning_1
## [1] "estimated parameter 'process[recruit_E].b0' was within 0.001 of upper bound 16.2"
## 
## $warning_2
## [1] "estimated parameter 'process[recruit_W].b0' was within 0.001 of upper bound 0.59"
## 
## $warning_3
## [1] "estimated parameter 'process[recruit_E].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_4
## [1] "estimated parameter 'process[recruit_W].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_5
## [1] "estimated parameter 'selectivity[CRsl].mu' was within 0.001 of lower bound 1"
## 
## $type
## [1] "warnings"
## 
## [1] ""
## [1] "Casal2 cppad_casal_flags_on model warnings"
## $warnings_found
## [1] 6
## 
## $warning_0
## [1] "Estimates were removed because of matching lower and upper bounds. Originally had 134 estimates, now have 133"
## 
## $warning_1
## [1] "estimated parameter 'process[recruit_E].b0' was within 0.001 of upper bound 16.2"
## 
## $warning_2
## [1] "estimated parameter 'process[recruit_W].b0' was within 0.001 of upper bound 0.59"
## 
## $warning_3
## [1] "estimated parameter 'process[recruit_E].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_4
## [1] "estimated parameter 'process[recruit_W].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_5
## [1] "estimated parameter 'selectivity[CRsl].mu' was within 0.001 of lower bound 1"
## 
## $type
## [1] "warnings"
## 
## [1] ""
## [1] "Casal2 cppad_casal_flags_off model warnings"
## $warnings_found
## [1] 6
## 
## $warning_0
## [1] "Estimates were removed because of matching lower and upper bounds. Originally had 134 estimates, now have 133"
## 
## $warning_1
## [1] "estimated parameter 'process[recruit_E].b0' was within 0.001 of upper bound 16.2"
## 
## $warning_2
## [1] "estimated parameter 'process[recruit_W].b0' was within 0.001 of upper bound 0.59"
## 
## $warning_3
## [1] "estimated parameter 'process[recruit_E].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_4
## [1] "estimated parameter 'process[recruit_W].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_5
## [1] "estimated parameter 'selectivity[CRsl].mu' was within 0.001 of lower bound 1"
## 
## $type
## [1] "warnings"
## 
## [1] ""
## [1] "Casal2 adolc_casal_flags_on model warnings"
## $warnings_found
## [1] 9
## 
## $warning_0
## [1] "Estimates were removed because of matching lower and upper bounds. Originally had 134 estimates, now have 133"
## 
## $warning_1
## [1] "estimated parameter 'process[recruit_E].b0' was within 0.001 of upper bound 16.2"
## 
## $warning_2
## [1] "estimated parameter 'process[recruit_W].b0' was within 0.001 of upper bound 0.59"
## 
## $warning_3
## [1] "estimated parameter 'process[recruit_E].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_4
## [1] "estimated parameter 'process[recruit_W].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_5
## [1] "estimated parameter 'selectivity[Enspsl].sigma_r' was within 0.001 of upper bound 50"
## 
## $warning_6
## [1] "estimated parameter 'selectivity[Wnspsl].sigma_r' was within 0.001 of upper bound 50"
## 
## $warning_7
## [1] "estimated parameter 'selectivity[CRsl].mu' was within 0.001 of lower bound 1"
## 
## $warning_8
## [1] "estimated parameter 'selectivity[SAsl].sigma_r' was within 0.001 of lower bound 1"
## 
## $type
## [1] "warnings"
## 
## [1] ""
## [1] "Casal2 adolc_casal_flags_off model warnings"
## $warnings_found
## [1] 9
## 
## $warning_0
## [1] "Estimates were removed because of matching lower and upper bounds. Originally had 134 estimates, now have 133"
## 
## $warning_1
## [1] "estimated parameter 'process[recruit_E].b0' was within 0.001 of upper bound 16.2"
## 
## $warning_2
## [1] "estimated parameter 'process[recruit_W].b0' was within 0.001 of upper bound 0.59"
## 
## $warning_3
## [1] "estimated parameter 'process[recruit_E].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_4
## [1] "estimated parameter 'process[recruit_W].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_5
## [1] "estimated parameter 'selectivity[sel_Whome].v{7}' was within 0.001 of upper bound 1"
## 
## $warning_6
## [1] "estimated parameter 'selectivity[Enspsl].sigma_r' was within 0.001 of upper bound 50"
## 
## $warning_7
## [1] "estimated parameter 'selectivity[CRsl].mu' was within 0.001 of lower bound 1"
## 
## $warning_8
## [1] "estimated parameter 'selectivity[SAsl].sigma_r' was within 0.001 of lower bound 1"
## 
## $type
## [1] "warnings"
## 
## [1] ""
## [1] "Casal2 adolc_casal_flags_on_low_tol model warnings"
## $warnings_found
## [1] 9
## 
## $warning_0
## [1] "Estimates were removed because of matching lower and upper bounds. Originally had 134 estimates, now have 133"
## 
## $warning_1
## [1] "estimated parameter 'process[recruit_E].b0' was within 0.001 of upper bound 16.2"
## 
## $warning_2
## [1] "estimated parameter 'process[recruit_W].b0' was within 0.001 of upper bound 0.59"
## 
## $warning_3
## [1] "estimated parameter 'process[recruit_E].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_4
## [1] "estimated parameter 'process[recruit_W].ycs_values{1999}' was within 0.001 of lower bound 0.06"
## 
## $warning_5
## [1] "estimated parameter 'selectivity[Enspsl].sigma_r' was within 0.001 of upper bound 50"
## 
## $warning_6
## [1] "estimated parameter 'selectivity[Wnspsl].sigma_r' was within 0.001 of upper bound 50"
## 
## $warning_7
## [1] "estimated parameter 'selectivity[CRsl].mu' was within 0.001 of lower bound 1"
## 
## $warning_8
## [1] "estimated parameter 'selectivity[SAsl].sigma_r' was within 0.001 of lower bound 1"
## 
## $type
## [1] "warnings"

1.4 Matching of outputs

Time series comparisons with CASAL base model results

## [1] "Catch time series base model comparison for run betadiff_casal_flags_on"
## [1] "Actual catches for Ensp1 match: yes"
## [1] "Actual catches for Wnsp1 match: yes"
## [1] "Actual catches for Ensp2 match: yes"
## [1] "Actual catches for Wnsp2 match: yes"
## [1] "Actual catches for Esp match: yes"
## [1] "Actual catches for Wsp match: yes"
## [1] ""
## [1] "Catch time series base model comparison for run betadiff_casal_flags_off"
## [1] "Actual catches for Ensp1 match: yes"
## [1] "Actual catches for Wnsp1 match: yes"
## [1] "Actual catches for Ensp2 match: yes"
## [1] "Actual catches for Wnsp2 match: yes"
## [1] "Actual catches for Esp match: yes"
## [1] "Actual catches for Wsp match: yes"
## [1] ""
## [1] "Catch time series base model comparison for run betadiff_casal_flags_on_low_tol"
## [1] "Actual catches for Ensp1 match: yes"
## [1] "Actual catches for Wnsp1 match: yes"
## [1] "Actual catches for Ensp2 match: yes"
## [1] "Actual catches for Wnsp2 match: yes"
## [1] "Actual catches for Esp match: yes"
## [1] "Actual catches for Wsp match: yes"
## [1] ""
## [1] "Catch time series base model comparison for run cppad_casal_flags_on"
## [1] "Actual catches for Ensp1 match: yes"
## [1] "Actual catches for Wnsp1 match: yes"
## [1] "Actual catches for Ensp2 match: yes"
## [1] "Actual catches for Wnsp2 match: yes"
## [1] "Actual catches for Esp match: yes"
## [1] "Actual catches for Wsp match: yes"
## [1] ""
## [1] "Catch time series base model comparison for run cppad_casal_flags_off"
## [1] "Actual catches for Ensp1 match: yes"
## [1] "Actual catches for Wnsp1 match: yes"
## [1] "Actual catches for Ensp2 match: yes"
## [1] "Actual catches for Wnsp2 match: yes"
## [1] "Actual catches for Esp match: yes"
## [1] "Actual catches for Wsp match: yes"
## [1] ""
## [1] "Catch time series base model comparison for run adolc_casal_flags_on"
## [1] "Actual catches for Ensp1 match: yes"
## [1] "Actual catches for Wnsp1 match: yes"
## [1] "Actual catches for Ensp2 match: yes"
## [1] "Actual catches for Wnsp2 match: yes"
## [1] "Actual catches for Esp match: yes"
## [1] "Actual catches for Wsp match: yes"
## [1] ""
## [1] "Catch time series base model comparison for run adolc_casal_flags_off"
## [1] "Actual catches for Ensp1 match: yes"
## [1] "Actual catches for Wnsp1 match: yes"
## [1] "Actual catches for Ensp2 match: yes"
## [1] "Actual catches for Wnsp2 match: yes"
## [1] "Actual catches for Esp match: yes"
## [1] "Actual catches for Wsp match: yes"
## [1] ""
## [1] "Catch time series base model comparison for run adolc_casal_flags_on_low_tol"
## [1] "Actual catches for Ensp1 match: yes"
## [1] "Actual catches for Wnsp1 match: yes"
## [1] "Actual catches for Ensp2 match: yes"
## [1] "Actual catches for Wnsp2 match: yes"
## [1] "Actual catches for Esp match: yes"
## [1] "Actual catches for Wsp match: yes"
## [1] ""

Derived quantities

SB0, SBcurrent, MSY, F_MSY, others…

1.5 Plots

Comparison plots

## [1] "CASAL base parameter correlation range (excluding 1.0): -0.991373 0.996882"

## [1] "CASAL sensitivity 1 parameter correlation range (excluding 1.0): -0.932422 0.996848"

## [1] "Casal2 betadiff_casal_flags_on parameter correlation range (excluding 1.0): -0.884321982666693 0.996651189974699"

## [1] "Casal2 betadiff_casal_flags_off parameter correlation range (excluding 1.0): -0.892527497796813 0.996650191207509"

## [1] "Casal2 betadiff_casal_flags_on_low_tol parameter correlation range (excluding 1.0): -0.936296735406878 0.996647376630237"

## [1] "Casal2 cppad_casal_flags_on parameter correlation range (excluding 1.0): 0 0"

## [1] "Casal2 cppad_casal_flags_off parameter correlation range (excluding 1.0): 0 0"

## [1] "Casal2 adolc_casal_flags_on parameter correlation range (excluding 1.0): -0.981865171360072 0.996644781288907"

## [1] "Casal2 adolc_casal_flags_off parameter correlation range (excluding 1.0): -0.884163492058679 0.996597746044801"

## [1] "Casal2 adolc_casal_flags_on_low_tol parameter correlation range (excluding 1.0): -0.888515743660313 0.999511857241577"